c ○ 2005 Springer Science + Business Media, Inc. Manufactured in The Netherlands. The Prom

International Journal of Computer Vision62(1/2),145–159,2005

c 2005Springer Science+Business Media,Inc.Manufacture

d in Th

e Netherlands.

The Promise and Perils of Near-Regular Texture?

YANXI LIU,YANGHAI TSIN AND WEN-CHIEH LIN

The Robotics Institute,Carnegie Mellon University,5000Forbes Ave.,Pittsburgh,PA15213,USA

yanxi@https://www.wendangku.net/doc/dd13440665.html,

ytsin@https://www.wendangku.net/doc/dd13440665.html,

wclin@https://www.wendangku.net/doc/dd13440665.html,

Received December10,2002;Revised June23,2003;Accepted July1,2003

First online version published in November,2004

Abstract.Motivated by the low structural?delity for near-regular textures in current texture synthesis algorithms, we propose and implement an alternative texture synthesis method for near-regular texture.We view such textures as statistical departures from regular patterns and argue that a thorough understanding of their structures in terms of their translation symmetries can enhance existing methods of texture synthesis.We demonstrate the perils of texture synthesis for near-regular texture and the promise of faithfully preserving the regularity as well as the randomness in a near-regular texture sample.

Keywords:near-regular texture,texture synthesis,lattice,texture analysis,symmetry groups

1.Motivation

Near-regular textures are common in our daily life.

They can be observed in man-made products,by hand

or by machine,ranging from buildings to fabrics,

as well as in nature and biological process of life

science(Feynman,1998;Chambers,1995;Senechal,

1995;Zee,1999;Hargittai and Hargittai,2000).Hu-

mans have an innate ability to perceive and take ad-

vantage of symmetry(Leyton,1992).Rao and Lohse

(1993)showed that regularity plays an important role

in human texture perception.However,it is not obvious

how to automate this powerful insight.

Mathematically speaking,regular texture refers to

periodic patterns that present non-trivial translation

symmetry,with the possible addition of rotation,re-

?ection and glide-re?ection symmetries(Miller Jr.,

1972;Coxeter,1980;Gr¨u nbaum and Shephard,1987).

When studying periodic patterns,a useful fact from

mathematics is the answer to Hilbert’s18th prob-

?This work is funded in part by an NSF research grant#

IIS-0099597.

lem:there is only a?nite number of symmetry

groups for all possible periodic patterns in dimension n

(Bieberbach,1910).When n=1there are seven frieze

groups,and when n=2there are17wallpaper

groups.Here group is referring to the symmetry group

of a periodic pattern.A symmetry group is composed of

transformations that keep the pattern setwise invariant.

In computer vision and computer graphics,the appli-

cation of this classic mathematics for regular or near-

regular pattern analysis has yet to be fully explored.

Only recently,have computer algorithms of symmetry

group classi?cation been developed for periodic pat-

terns in real images under Euclidean(Liu and Collins,

2000;Liu et al.,2004)and af?ne transformations(Liu

and Collins,2001),based on a careful analysis of the

basic tile shapes of regular patterns.In computer graph-

ics,one interesting recent work(Kaplan and Salesin,

2000)is to?nd Escher-like tilings by deforming a sin-

gle closed planar?gure to tile a plane.

Near-regular texture is referring to textures that

are not strictly symmetrical.The irregularity can be

caused by various statistical departures from regular

textures.These departures can happen along different

146Liu,Tsin and

Lin

Figure 1.Symmetry or regularity of images spans a continuous,multi-dimensional space.

dimensions of symmetry (Liu,2001),for example,color (single,multi)(Tsin et al.,2001),intensity (ir-regular statistical alterations,random noise),global or local geometric deformations (af?ne,projective,ran-dom)(Liu and Collins,2000,2001),and resolution.See Fig.1from Liu (2001)for some examples of symmetry dimensions.The focus of this paper is on faithful tex-ture synthesis of near-regular textures where departure from regularity is primarily caused by statistical color and intensity variations,while the underlying struc-tural regularity remains.There are many examples of this type of near-regular textures,e.g.brick walls,tiled ?oors,carpets,and woven sheets,where the texture pat-terns (each brick,tile,straw or bamboo strip)vary only locally.The idea of viewing a random texture as a dis-torted version of a regular texture was expressed in an early paper by Zucker (1976).More recently,we have demonstrated a computational model for near-regular textures that vary along geometry,lighting and color dimensions (Liu et al.,2004).

Existing work on texture synthesis has achieved impressive results for a variety of different types of textures (e.g.,De Bonet,1997;Efros and Leung,1999;Ashikhmin,2001;Efros and Freeman,2001;Hsu and Wilson,1998;Wei and Levoy,2000;Hertzmann et al.,2001;Xu et al.,2001;Liang et al.,2001;Zhu et al.,2000;Kwatra et al.,2003;Cohen et al.,2003).These texture synthesis algorithms share a common theme of local neighborhood-based statistical approaches.Distinctions can be drawn be-tween approaches that constructively establish statis-tical models for the input texture (Cross and Jain,1983;Zhu et al.,1997)versus others that seek to ?nd matching joint statistics directly in the input samples (De Bonet,1997;Portilla and Simoncelli,

2000;Zhu et al.,2000).More recently,non-parametric estimation of texture PDFs has become popular (Efros and Leung,1999;Wei and Levoy,2000;Efros and Freeman,2001;Liang et al.,2001).These tex-ture synthesis algorithms are relatively simple to implement,fast to run (Wei and Levoy,2000;Liang et al.,2001)and able to reproduce a large variety of textures,from regular to random ,as claimed by the au-thors.However,after reviewing the results of existing work applied to near-regular textures,we observe that the structural regularity is usually not well preserved in the synthesized texture.This is especially true when the input sample has interlocking near-regular patterns,or is oriented obliquely.For example,we have not yet seen an existing texture synthesis algorithm that pre-serves the regularity in a brick wall sample (Fig.2(a)).In addition,the structural property of near-regular tex-tures has not been used as an objective measure for texture synthesis algorithms (Lin et al.,2004).

This situation motivates us to propose and implement an alternative texture synthesis method for near-regular texture that is particularly faithful to its structural prop-erty while preserving the randomness observed in the input data.Figures 2and 3demonstrate two sample results from our texture synthesis algorithm in contrast to the texture synthesis results reported in Efros and Freeman (2001).

Section 2de?nes basic properties of regular texture such as generating tile,symmetry groups and lattice types.In Section 3we explain our texture analysis and synthesis algorithm and demonstrate some experimen-tal results.Section 4discusses several relevant issues in near-regular texture synthesis,from window size to the concept of textons.Section 5concludes with a sum-mary and future research directions.2.

Regular Texture Analysis

A symmetry of a 2D periodic pattern P is a distance preserving mapping g :R 2×I ?R 2×I such that g (P )=P ,where I can either be gray values in the range of [0,255]or RG

B intensity values.It can be proven that all symmetries of P form its symmetry group.All the translation symmetries of a periodic pat-tern form its translation subgroup,a group generated by two linearly independent,shortest translation sym-metries t 1, t 2of P (Schattschneider,1978).Mathemat-ically speaking,symmetry groups are de?ned only for

periodic patterns of in?nite extent.In practice,we an-alyze a periodic pattern bounded within a ?nite image area,and thus use the concept of symmetry group G

The Promise and Perils of Near-Regular Texture147

Figure2.(a)input texture sample.(b)texture synthesis result from Efros and Freeman(2001).This is one of the best results on brick wall texture synthesis that we can?nd.However,the regularity in the input texture sample is not faithfully preserved in the synthesized texture:two short bricks are stacked together and there are more than two brick sizes in the synthesized image.(c)the texture synthesis result of our algorithm proposed in this paper.

Figure3.(a)input texture sample.(b)texture synthesis result from Efros and Freeman(2001).Straw pattern:one vertical line is terminated midway.(c)the texture synthesis result of our algorithm proposed in this paper.

148Liu,Tsin and Lin

of P to mean G is the symmetry group of an in?nite periodic pattern for which P is a ?nite region with more than one period.

Each 2D regular texture is a 2D periodic pattern that contains a non-empty parallelogram T .The or-bit of T under the action of its translation symme-try subgroup produces simultaneously a covering (no gaps)and a packing (no overlaps)of the original pat-tern (Gr¨u nbaum and Shephard,1987;Schattschneider,1978).We call the smallest such parallelogram the tile of the texture.For a given regular texture its tile is uniquely de?ned in shape,size,and orientation but not in location,thus its pixelwise intensity and color con-tent may vary,depending on where the lattice of the texture pattern is anchored.

A mature mathematical theory for wallpaper-like regular texture has been known for over 100years (Fedorov,1885;Gr¨u nbaum and Shephard,1987),namely the theory of wallpaper groups.1For monochrome planar periodic patterns,there are sev-enteen wallpaper groups describing patterns extended by two linearly independent translational generators.Despite the in?nite variety of regular texture instanti-ations,this ?nite set of symmetry groups and their 17corresponding lattice/tile structures completely char-acterize the possible structural symmetry of any 2D periodic pattern.There are only ?ve possible lattice shapes (Coxeter and Moser,1980),therefore ?ve tile shapes ,and they form a shape hierarchy (Fig.4):1.parallelogram,2.rectangular,3.rhombic,4.square,and 5.

hexagonal.

Figure 4.There are only ?ve possible types of tiles in 2D regular textures.

Each lattice unit or tile shape is a parallelogram.A rectangular tile has angles of 90o .A rhombic tile has equal-length edges.Square and hexagonal tiles are spe-cial cases of rectangle and rhombic,respectively.

Work in structural texture analysis (Enrich and Foith,1978;Lu and Fu,1978)is also based on the idea of a unit pattern together with a set of well-de?ned placement rules.However,its generality and computa-tional tractability are limited:unit patterns are either re-gions centered about a local maximum that is bounded on all sides by local minima (Enrich and Foith,1978)or square texture regions with an unspeci?ed window size (Lu and Fu,1978).Conners and Harlow (1980)use mathematical tiling theory for the analysis of texture,but they do not take advantage of the complete char-acterization of lattice types and the inner structures of 2D regular texture afforded by wallpaper groups,and their characterization of pattern elements is dominated by the inertia feature alone.

One essential element in our method is to acknowl-edge the regularity in a near-regular texture by ?rst locating the generating “tile”precisely.This computa-tional effort is guided by the basic principles and un-derstanding of tiles and their symmetries,as concisely summarized in their wallpaper groups.In order to ?nd tiles in a given 2D near-regular pattern we developed an algorithm in Liu and Collins (2000)and re?ned in Liu et al.(2004),based on regions of dominance ,for locating the underlying lattice of a given pattern.Figure 5shows the variations of shapes,sizes and ori-entations of lattices automatically generated from three real-world near-regular patterns.In addition,the gener-ating translation vectors and a typical tile are indicated

as an example on one of the three textures.The t 1, t 2

translational symmetries of a regular pattern alone ?x the size,shape and orientation of the lattice,but leave open the question of where the lattice is located on the pattern.Any offset of the lattice on a pattern carves the pattern into a set of similar tiles,any one of which can generate the whole 2D pattern.For perception pur-poses (Liu and Collins,2001;Liu et al.,2004),a motif (a representative tile)can be chosen that re?ects the symmetry property of the whole pattern.For synthesis purposes,on the other hand,the tiles could be chosen to optimize the “blending”effects (Section 3.1).3.

Our Method for Texture Synthesis

Perfect regularities are rarely found in the real world,while varying degrees of deviation from regularity

The Promise and Perils of Near-Regular Texture

149

Figure5.Examples of imperfect,real-world near-regular patterns overlayed with automatically detected underlying lattices using an algorithm

developed in Liu et al.(2004).Notice the different shape,size and orientations of the tiles.The arrows drawn on the middle image give an

example of the two shortest generating translations t1, t2for this texture pattern.The region bounded by the two vectors(enclosed by the two vectors and two dotted lines)indicates a tile for this pattern.For each near-regular texture,there exists a well-de?ned tile that is bounded by the

two linearly independent translations of its wallpaper pattern.

are common to observe.Our research interest is to

capture both regularity and randomness by combin-

ing the mathematical theory of regular patterns with

statistical modeling of data in texture analysis and

synthesis.

We treat a set of tiles carved by the detected lattice as

multiple samples of the same tile.We de?ne these tiles

as minimum tiles{t i}since by de?nition of regular pat-terns there are no2D regions smaller than these tiles that

can tile the whole texture pattern under its translation

subgroup.Correspondingly,we de?ne a set of maxi-

mum tiles{T i}by circumscribing each minimum tile t i with the smallest rectangularly shaped convex hull. Note that depending on the shape and orientation of the t i’s,maximum tiles T i can be in any possible orienta-tion and aspect ratio.The minimum(maximum)tile set also contains tiles centered on half-way shifted lattice points(i.e.at locations((n+1/2) t1,(m+1/2) t2)from the anchored lattice position,where m,n are integers). For texture synthesis,at each time a tile is randomly chosen from these tile sets.This process provides the promise of capturing statistical color and intensity vari-ations from different tiles,which can give the generated texture more natural appearance,while reproducing its regularity.3.1.Algorithm for Texture Synthesis

of Near-Regular Patterns

Input:a sample near regular texture S

Output:a synthesized texture S statistically similar to S.

Stage1(analysis):

?First determine the translational symmetry vectors t1, t2from the given sample near-regular texture pat-tern.In our experiments,these vectors can either be(1)computed automatically(Liu and Collins, 2001;Liu et al.,2004);(2)indicated by the user by clicking on three nearest corresponding points of the texture,or(3)computed?rst and veri?ed by the user.

?Determine where the lattice should be anchored such that all the minimum tiles t i are uniquely de?ned.This is one parameter that the user can control to make the boundary of the tiles align with low frequency regions for the bene?t of better blending results.In our experiments,most lattice locations have been hand-located.

?For each t i construct the corresponding maximum tile sets T and T h.T contains all the T i s centered on the

150Liu,Tsin and

Lin

Figure 6.The sample tiles (rhombic shaped tiles are minimum tiles {t i }and rectangle shaped tiles are maximum tiles {T i })are shown,they are carved from the input brick texture.(a)and (b)show two different lattice positions.

lattice points,and T h contains all the T i s centered on the half-way shifted lattice points.

Figure 6shows the brick wall sample as an example.Each rhombic shaped tile t i is enclosed by a rectangular maximum tile.Stage 2(synthesis):

1.Start from the top left corner with a random tile chosen from T .

2.One tile is added at a time into the synthesized tex-ture in a scanline order along the direction of t 1+ t 2

with a step size of |( t 1+ t 2)/2|.When the process

reaches the right boundary of the desired image size,

one tile is placed in the direction of t 2? t 1with a step

size of |( t 2? t 1)/2|from the leftmost synthesized

tile of the current row.

3.At each lattice or half-way lattice point,alter-natively select the T or T h tile set.For each tile in the selected tile set,we compute its color difference to the existing synthesized im-age in the overlapping region where the tile is going to be pasted.The error function is:F error (im 1,im 2)= i ,j (dist (im 1(i ,j ),im 2(i ,j )))where dist (im 1(i ,j ),im 2(i ,j ))= (abs (R i 1?R i 2)+abs (G i 1?G i 2)+abs (B i 1?B i 2))and R ,G ,B are rgb values of a pixel.A candidate tile set is formed by selecting those tiles that have an RGB intensity difference less than a threshold.A tile is then ran-domly picked from the candidate tile set.If the can-didate set is empty,we pick the tile with minimum

The Promise and Perils of Near-Regular Texture 151

error to paste to the synthesized image.The size of the candidate tile set varies at every lattice point.

4.Register the selected candidate tile using a correlation-based method such that small move-ments around the current lattice point are possible.

https://www.wendangku.net/doc/dd13440665.html,e dynamic programming to “stitch”together the overlapping tiles in a similar manner as described in Efros and Freeman (2001).The dynamic pro-gramming technique is applied separately along the horizontal and vertical directions.

6.When pasting a tile to the existing image,blending is applied to the boundaries where the dynamic pro-gramming along horizontal and vertical directions may have con?icting decisions.In other words,all pixels on the boundary of the selected tile and ex-isting synthesized texture are either results of dy-namic programming or blending.The blending is done on a padded region around the boundary of the selected tile t i and existing synthesized tile t ,based on this formula:w (i ,j )×t i (i ,j )+(1?w (i ,j ))×t (i ,j )where 0≤w (i ,j )≤1depend-ing on the distance from the pixel (i ,j )to the

boundary.

Figure 7.(a)and (b)random sampling from tile sample sets (Figs.2and 3)using our texture synthesis method,which preserve both the near-regular nature of the texture and the variations across tiles.The symmetry group of both patterns is classi?ed as cmm containing translation,rotation,re?ection and glide-re?ection symmetries (Liu and Collins,2000).(c)and (d)direct tiling results.Though the regularity of the input texture is preserved,the synthesized texture does not re?ect the intensity variations in the input texture.

7.Repeat steps 2through 6until the whole image is synthesized.The reason we use maximum tiles instead of mini-mum tiles for synthesis is to have redundant overlap-ping regions for a smoother transition on the tile https://www.wendangku.net/doc/dd13440665.html,ing this method,each tile has half to three quarters of overlap with the currently synthesized im-age.As a result,correlation-based registration can be done robustly.However,as departure from regularity in the texture increases,one can expect less coherence in the synthesized image.It takes about 20seconds to synthesize an image of size 544by 565on a 2.2Ghz PC,using non-optimized Matlab code.

3.2.Experimental Results

Images (c)in Figs.2and 3show our synthesized results in comparison with the corresponding results from Efros and Freeman (2001).Figure 6shows both the minimum and the maximum tiles used in the brick wall example (Fig.2).Figure 7demonstrates the difference between naive direct tiling and our random selection

152Liu,Tsin and

Lin

Figure 8.More examples on texture synthesis using our proposed approach.

method.Figure 8shows more sample results of our method.Figures 9–11demonstrate the synthesized re-sults of three near regular textures where the lattices are automatically generated as shown in Fig.5.These experimental results re?ect our intention of preserv-ing the near-regular structure of the input texture as well as the statistical variations across and within the tiles.

Due to the blending procedure,the synthesized tex-ture may appear not as sharp as the input texture (e.g.Image (c)of Fig.3).The top result shown in Fig.8may appear more regular than the input texture as a result of using an error threshold that is too tight after a random candidate tile selection.There is a tradeoff be-tween allowing more variations in the synthesized tex-ture and keeping the textures over the stitching bound-aries more similar to each other.However,there is a natural agreement between the probability of a tile ap-pear in the input texture and its chance to appear in the synthesized texture.For example,tiles containing holes in the rug textures (Fig.5)have a lesser chance to be selected than those similar-looking tiles in the

The Promise and Perils of Near-Regular Texture

153

Figure 9.The synthesized result from one of the real-world near-regular textures shown in Fig.5,where the underlying lattices are automatically detected using an algorithm developed in Liu et al.

(2004).

Figure 10.The synthesized result from one of the real-world near-regular textures shown in Fig.5,where the underlying lattices are automatically detected using an algorithm developed in Liu et al.(2004).

input texture,due to their oddness in the tile popula-tion.As a result,the holes may not appear in the output texture at all as shown in Figs.10and 11.When the direction of t 1+ t 2is not parallel with horizontal and

vertical axes of the image,for simplicity in our ex-periments the shape of the maximum tile remains to

be an upright rectangle containing the minimum tile (Fig.6).An alternative,perhaps better,choice is to use

154Liu,Tsin and

Lin

Figure 11.The synthesized result from one of the real-world near-regular textures shown in Fig.5,where the underlying lattices are automatically detected using an algorithm developed in Liu et al.(2004).

the coordinate system of the texture de?ned by the min-imum tile shape to de?ne the shape of the maximum tile.

4.Discussion

One obvious limitation of this work is its focus on near-regular texture alone.Nevertheless,several fun-damental issues for texture understanding and synthe-sis seem to be related.Firstly,with respect to the very different properties of different textures (random ver-sus regular)should we treat all textures uniformly?If not,how should we combine different methodologies together?Secondly,almost all the texture synthesis al-

gorithms have to de?ne a window,sometime called patch,and which we call a tile,to sample the orig-inal input textures.(In this paper,we use the word window,patch and tile interchangeably).What are the basic variables involved in choosing a window,and what are their impacts?Thirdly,for near-regular tex-tures,can we do better than what has been proposed here?What will happen if we go beyond translation symmetry and investigate the effect of rotation,re?ec-tion and glide-re?ection symmetries?and how may this be related to the concept of texton for near-regular texture?

In the following,under the context of texture synthe-sis,we shall elaborate on each of these topics in more detail.

The Promise and Perils of Near-Regular Texture155

4.1.Regular Texture Versus Random Texture

It is beyond the topic of this paper to investigate the def-inition of texture and whether regular or near-regular patterns should be considered as texture.However, near-regular texture does have its own special prop-erties and relevant mathematical theories that can be, and actually have to be,taken into consideration in or-der to carry out the texture synthesis properly.On the other hand,it is also a reasonable concern that if regu-larity dominates the synthesized texture to the extreme of regular tiling,there will be no meaning in texture synthesis.

One fundamental principle in texture synthesis we are following is to be faithful to the input sample texture by respecting both its regularity and statistical random-ness.One of the perils when dealing with near-regular texture is the temptation to use direct tiling(of a tile) to?ll the whole2D image.Though tiling is the cen-tral theme and appropriate means for many artistic and design tasks(Washburn and Crowe,1991;Gr¨u nbaum and Shephard,1987),it is usually not suited for pro-viding natural visual effects in the context of texture synthesis.The results from simple tiling are overly reg-ular,usually more so than the original input sample (Fig.7).

The two perils of near-regular texture are:

1.random treatment:ignoring the special property of

regularity,thus regularity(a global property)is no longer preserved(images(b)in Figs.2and3); 2.regular treatment:only recognizing that the tex-

ture is regular,thus ended up repeating a single tile (Fig.7).

Alternatively,one can avoid both of these two poten-tial traps.There are many ways to combine the treat-ment of near-regular texture proposed here with exist-ing local-neighborhood methods that are known to be particularly effective for random textures.One way is to build a texture regularity classi?er F.Given a sam-ple texture T,if F(T)=1exceeds a certain thresh-old,use our near-regular texture algorithm,otherwise resort to one of the local-neighborhood methods.Peo-ple have already experimented with such classi?ers. For example,Chetverikov(2000)provides a score for a textured pattern that seems to be consistent with hu-man perception.See Fig.12from Chetverikov(2002) for an example of regularity scores.Our lattice detec-tion algorithm(Liu and Collins,2000)or other future robust lattice extraction algorithms can also serve as a periodicity measure.In this manner,both the near-regular end and the random end of the textures will be well covered.The question then will become:how to treat those textures that are in the middle of the tex-ture spectrum.We foresee a continuous spectrum from regular to random texture,but where to draw the line be-tween regular,near-regular,near-random and random remains an open problem.It would be interesting to quantify how strong the regularity in a texture should be for the proposed texture synthesis method to be most effective.

4.2.Will the Regularity in the Input Texture

be Preserved by Increasing Window Size

During Texture Synthesis?

Despite common belief,the answer to the above ques-tion is no.Figure13from Efros and Leung(1999)does show a trend towards regularity with the increase of the window size,however,it does not show that the regu-larity of the input texture can be reproduced with the increase of the window size.As a matter of fact,if one looks at the right-most synthesized result in Fig.13 carefully,it becomes obvious that the regularity pro-duced in the synthesized texture with the larger win-dow size is not the same kind of structural regularity presented in the input texture.Even though the smaller sized bricks occur in the input texture due to cut-offs at image borders,there is suf?cient evidence to indicate that the input texture has bricks of only one size.

A local neighborhood-based approach is incapable of perceiving texture structure beyond the image bor-ders,therefore it is not surprising that the synthesized texture reproduces what it can observe,and thus we see the mix of short bricks with the longer ones.Im-age quilting(Efros and Freeman,2001)as a typical local approach allows variations around the overlap-ping boundary regions.When two patches are placed too close to each other due to an inappropriate window size,the algorithm can only maximize the similarity and smoothness locally to achieve a better looking lo-cal boundary,even though a global transformation is required to reproduce the similar spacing indicated in the original pattern.One can push the window size ar-gument to the extreme:imagine using the whole input texture as the largest possible patch,even then the reg-ularity of the input texture will still not be preserved, unless the cut-offs happen right at the matching line (e.g.the short bricks happen to have half-brick length in Fig.13).The input texture has to be a super tile,

156Liu,Tsin and

Lin

Figure 12.Image from Chetverikov (2002)shows the regularity scores for various types of

textures.

Figure 13.Image from Efros and Leung (1999)shows that the synthesized texture becomes more regular with the increase of the window size.The question is:whether the regularity in the input sample will be reproduced by increasing the window size?The answer is:in general,No .

otherwise by putting its own copies together the regular pattern in the original texture (with a smaller generating tile)still can not be reproduced without discontinuity.

4.3.

How to Determine the Sample Window Shape Used for Texture Synthesis?

It is stated in Efros and Freeman (2001)that:Determining precisely what are the patches for a given texture and how they are put together is still

an open problem ...let us de?ne the ...(patch)...to be a square block of user-speci?ed size ...For lack of a better choice of window shapes,an upright square window is a common choice for many texture synthesis algorithms (Efros and Freeman,2001;Wei and Levoy,2000;Xu et al.,2001;Liang et al.,2001).The reason that local texture synthesis algorithms work on certain near-regular textures (patterns of dots or knots,for example)is due to a judicious choice of the window size and shape that happens to match the tile shape and orientation of the input sample.In the case

The Promise and Perils of Near-Regular Texture

157

Figure14.For this pattern(p6m,one of the17wallpaper groups patterns),only the triangle region is needed to recover the whole image through rotation,re?ection and translations.Thus much smaller tile sizes and more sample numbers can be used for texture synthesis of better quality.

of dots and knots(Figs.3and4in Efros and Freeman, 2001),it is an upright square;and in the case of soup cans and rows of windows,it is an upright rectangle such that a proper square can serve as a super tile(Fig.4 in Efros and Freeman(2001)).Conversely,an improper choice of window size and shape usually causes failure in faithful texture synthesis(e.g.images(b)in Figs.2 and3from Efros and Freeman(2001)).

A key factor in reproducing regularity is to recog-nize,simultaneously,the shape,orientation and size of a basic tile of the input near-regular texture.This is the attempt we make in our texture synthesis method (Fig.5).One advantage of our approach is that the tile shape(not necessarily a square),orientation(not nec-essarily upright),and size are determined up front,ex-plicitly,and customized to each input near-regular tex-ture pattern(Fig.5).Even though the input texture’s color and intensity may vary randomly,recognizing the underlying structural regularity provides a skeleton for the appropriate texture displacement while allowing color and intensity variations.We have demonstrated the feasibility of this approach in Section3.2.

4.4.Go Beyond Translational Symmetry and How

it is Related to the Concept of Texton

When one really understands the making of a periodic pattern and its generating regions (Schattschneider,1978),modi?cations can be made to direct tiling such that more natural appearance can be achieved.In particular,we have only used translational symmetry in this paper,rotation,re?ection and glide re?ection symmetries can also be used to generate pat-terns from much smaller tiles(Fig.14).This means that a much larger sample set of observed statistical vari-ations can be obtained in a principled and controlled manner.

In many texture related papers(e.g.,Zhu et al.,2002) the concept of a“texton”has been suggested.Texton is referring to the atomic element in a texture.There exists an interesting interplay between what is a texton and which group of transformations that one is consid-ering.In the case at hand(Fig.14),if we only consider the translation subgroup of the symmetry group of the texture pattern,the texton would be the parallelogram for hexagonal shape shown in the lower right corner of Fig.4.If we consider the whole symmetry group of the texture pattern,the corresponding texton then becomes the small triangle indicated in Fig.14.Near-regular textures provide a more structured environment for ex-ploring the elusive concept of multi-layered textons.

5.Conclusion and Research Directions

In this paper,we provide a new method for near-regular texture synthesis.Our method differs from most local-neighborhood approaches to texture synthesis in that it ?rst does a texture structure analysis by identifying the speci?c tile shape of the given texture.Our approach also separates the treatment of spatial layout regularity

158Liu,Tsin and Lin

(tiles)from the intensity/color variations(the content of a tile).A special treatment for near-regular texture in texture synthesis has been a missing piece in the texture synthesis puzzle.

We point out that it is actually a misconception that the regularity in the input sample will be reproduced when the window size is large enough.It should be re-alized by now that the regularity preservation problem can not be solved by adjusting window size alone. We are investigating the use of a richer set of symme-tries residing in near regular texture beyond translation. Our long term goal is to model a continuous texture spectrum from regular to near-regular to chaotic pat-terns,and to study texture variations along different dimensions of symmetry(Liu,2001).

Acknowledgment

This research is partially funded by an NSF research grant#IIS-0099597.We highly appreciate the con-structive comments given by two anonymous review-ers.Dr.Liu thanks Professor W.T.Freeman,Dr.A.A. Efros and Dr.R.T.Collins for helpful discussions. Note

1.These groups are also called two dimensional Crystallographic

groups(Henry and Lonsdale,1969).

References

Ashikhmin,M.2001.Synthesizing natural textures.In ACM Sympo-sium on Interactive3D Graphics,pp.217–226. Bieberbach,L.1910.¨Uber die Bewegungsgruppen der n-dimensional en Euklidischen R¨a ume mit einem endlichen Fun-damental bereich.G¨o ttinger Nachrichten,pp.75–84. Chambers,D.A.(ed.).1995.DNA:The Double Helix:Perspective and Prospective at Forty Years.New York Academy of Sciences: New York.

Chetverikov,D.2000.Pattern regularity as a visual key.Image and Vision Computing,18:975–986.

Chetverikov,D.2002.Fundamental structural properties of textures. PhD thesis,MTA SZTAKI,Budapest.

Cohen,M.F.,Shade,J.,Hiller,S.,and Deussen,O.2003.Wang tiles for image and texture generation.ACM Transactions on Graphics, 22(3):287–294.

Conners,R.W.and Harlow,C.A.1980.Toward a structural tex-tural analyzer based on statistical methods.CGIP,12(3):224–256.

Coxeter,H.S.M.1980.Introduction to Geometry,2nd edn.Wiley, New York.

Coxeter,H.S.M.and Moser,W.O.J.1980.Generators and Relations for Discrete Groups,4th edn.Springer-Verlag:New York.Cross,G.R.and Jain,A.K.1983.Markov random?eld texture mod-els.IEEE Trans.PAMI,5:25–39.

De Bonet,J.S.1997.Multiresolution sampling procedure for anal-ysis and synthesis of texture image.In SIGGRAPH Proceedings, pp.361–368.

Efros,A.A.and Freeman,W.T.2001.Image quilting for texture syn-thesis and transfer.In SIGGRAPH,pp.35–42.

Efros, A.A.and Leung,T.K.1999.Texture synthesis by non-parametric sampling.In International Conference on Computer Vision.

Enrich,R.and Foith,J.P.1978.A view of texture topology and texture https://www.wendangku.net/doc/dd13440665.html,puter Graphics Image Processing,8:174–202.

Fedorov, E.S.1885.The elements of the study of?gures. [Russian](2)21.In Zapiski Imperatorskogo S.Peterburgskogo Mineralogichesgo Obshchestva[Proc.S.Peterb.Mineral.Soc.], pp.1–289.

Feynman,R.P.1998.Six Not-so-Easy-Pieses:Einstein’s Rela-tivity,Symmetry,and Space-Time.Perseus Press:Cambridge, MA.

Gr¨u nbaum,B.and Shephard,G.C.1987.Tilings and Patterns,W.H. Freeman and Company:New York.

Hargittai,I.and Hargittai,M.2000.In Our Own Image:Personal Symmetry in Discovery.Kluwer Academic Publishers. Henry,N.F.M.and Lonsdale,K.(eds.).1969.International Tables for X-ray Crystallography,Vol.1,Symmetry Groups.The Kynoch Press:England,The International Union of Crystallography. Hertzmann,A.,Jacobs,C.E.,Oliver,N.,Curless,B.,and Salesin, D.H.2001.Image analogies.In SIGGRAPH.

Hsu,T.I.and Wilson,R.1998.A two-component model of tex-ture for analysis and synthesis.IEEE Trans.on Image Processing, 7(10):1466–1476.

Kaplan,C.S.and Salesin,D.H.2000.Escherization.In the27th In-ternational Conference on Computer Graphics and Interactive Techniques.

Kwatra,V.,Schodl,A.,Essa,I.,Turk,G.,and Bobick,A.2003. Graphcut textures:Image and video synthesis using graph cuts. ACM Transactions on Graphics,22(3):277–286.

Leyton,M.1992.Symmetry,Causality,Mind.The MIT Press: Cambridge,MA.

Liang,L.,Liu,C.,Xu,Y.Q.,Guo,B.,and Shum,H.Y.2001.Real-time texture synthesis by patch-based sampling.ACM Transactions on Graphics(TOG),20(3):127–150.

Lin,W.C.,Hays,J.,Wu,C.,Kwatra,V.,and Liu,Y.2004.A com-parison study of four texture synthesis algorithms on regular and near-regular textures poster at SIGGRAPH2004.Under review at ACM Transactions on Graphics.CMU Robotics Institute Techni-cal Report CMU-RI-TR-04-01,pp.1–59.

Liu,https://www.wendangku.net/doc/dd13440665.html,putational symmetry.In Symmetry2000,I. Hargittai and https://www.wendangku.net/doc/dd13440665.html,urent(Eds.).vol.80chapter21,Wenner-Gren International Series,Portland,London,pp.231–245.ISBN I855781492.

Liu,Y.and Collins,R.T.2000.A computational model for repeated pattern perception using frieze and wallpaper groups.In Com-puter Vision and Pattern Recognition Conference(CVPR’00), IEEE Computer Society Press:Hilton Head,SC,pp.537–544. (https://www.wendangku.net/doc/dd13440665.html,/pubs/pub3302.html).

Liu,Y.and Collins,R.T.2001.Skewed symmetry groups.In Pro-ceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition(CVPR’01),IEEE Computer

The Promise and Perils of Near-Regular Texture159

Society Press:Kauai,HI,pp.872,879.(https://www.wendangku.net/doc/dd13440665.html,/ pubs/pub3815.html).

Liu,Y.,Collins,R.T.,and Tsin,Y.2004.A computational model for periodic pattern perception based on frieze and wallpaper groups. IEEE Transaction on Pattern Analysis and Machine Intelligence, 26(3):354–371.

Liu,Y.,Lin,W.C.,and Hays,J.2004.Near-regular texture analysis and manipulation.ACM Transactions on Graphics,23(3):368–376.

Lu,S.Y.and Fu,K.S.1978.A syntactic approach to texture analysis. Computer Graphics Image Processing,7:303–330.

Miller,W.Jr.1972.Symmetry Groups and Their Applications. Academic Press:New York.

Portilla,J.and Simoncelli,E.2000.A parametric texture model based on joint statistics of complex wavelet coef?cients.Int.Journal of Comp.Vision,40(1):49–71.

Rao,A.R.and Lohse,G.L.1993.Identifying high level features of texture perception.CVGIP:Image Processing,55:218–233. Schattschneider,D.1978.The plane symmetry groups:Their recog-nition and notation.American Mathematical Monthly,85:439–450.

Senechal,M.1995.Quasicrystals and Geometry.Cambridge Uni-versity Press.

Tsin,Y.,Liu,Y.,and Ramesh,V.2001.Texture replacement in real images.In Proceedings of IEEE Computer Society Confer-

ence on Computer Vision and Pattern Recognition(CVPR’01), vol.II,pp.539–544(https://www.wendangku.net/doc/dd13440665.html,/ytsin/research/ texture replacement/index.html),Kauai,IEEE Computer Society Press.

Washburn,D.K.and Crowe,D.W.1991.Symmetries of Culture: Theory and Practice of Plane Pattern Analysis.University of Washington Press.

Wei,L.Y.and Levoy,M.2000.Fast texture synthesis using tree-structured vector quantization.In SIGGRAPH,pp.479–488.

Xu,Y.Q.,Zhu,S.C.,Guo,B.N.,and Shum,H.Y.2001.Asymptoti-cally admissible texture synthesis.In International Workshop on Statistical and Computational Theories of Vision.

Zee,A.1999.Fearful Symmetry.Princeton University Press. Zhu,S.C.,Guo,C.E.,Wu,Y.N.,and Wang,Y.Z.2002.What are tex-tons.In Proceeding of European Conference on Computer Vision, Copenhagen,Denmark.

Zhu,S.C.,Liu,X.,and Wu,Y.2000.Exploring texture ensembles by ef?citn markov chain monte carlo.IEEE Transaction on PAMI, 22(6).

Zhu,S.C.,Wu,Y.,and Mumford,D.B.1997.Minimax entropy prin-ciple and its application to texture modeling.Neural Computation, 9:1627–1660.

Zucker,S.W.1976.Toward a model of texture.CGIP,5(2):190–202.

期刊在线投稿审稿管理系统需求规格说明书

期刊在线投稿审稿管理系统需求规格说明书 -标准化文件发布号：（9556-EUATWK-MWUB-WUNN-INNUL-DDQTY-KII

期刊在线投稿审稿管理系统需求规格说明书 学生姓名：xx 学生学号：xxxxxx 所在班级：12级计科 一、概述 1.1系统简介 数字化出版时代的到来，读者获取信息的维度不断拓宽，传统的投稿审稿模式已不能满足用户需求，也不能为期刊社或文学类网站赢得竞争优势。 此时，采用在线方式完成网上稿件征集、投稿、校稿、审稿，除了可以加快稿件处理的速度，还可以使整个流程公开化、公正化、透明化，方便了现实用户。 1.2用户简介 （1）投稿人：知名作家或文学爱好者（已注册） （2）审稿人：知名报社编辑、知名作家或网站编辑（已注册） （3）普通用户：已注册并登录网民 （4）游客：未登录网民 （5）系统管理员：网站技术工作人员（已注册） 1.3项目的要求和目标 要求： （1）描述项目的业务信息 （2）分析项目的管理工作的要求 （3）列出实体、联系 （4）指出实体和联系的属性 （5）画出E-R图 （6）画出层次方框图 （7）创建数据流程图 （8）建立数据字典 目标： （1）实现普通用户、投稿人、审稿人的信息管理 （2）实现稿件类型、稿件信息的管理

（3）实现稿件的审阅过程管理 （4）创建存储过程，统计指定作者的稿件信息 （5）创建规则，使得作者的E-Mail必须满足电子邮件的基本格式 （6）建立数据库相关表之间的参照完整性约束。 1.4术语定义 数据字典：数据字典是指对数据的数据项、数据结构、数据流、数据存储、处理逻辑、外部实体等进行定义和描述，其目的是对数据流程图中的各个元素做出详细的说明。 E-R图：E-R图也称实体-联系图(Entity Relationship Diagram)，提供了表示实体类型、属性和联系的方法，用来描述现实世界的概念模型。 1.5参考资料 张海藩软件工程导论第5版清华大学出版社2008 1.6相关文档 软件开发计划书 1.7版本更新信息 表1 版本更新记录 二、现有系统定义 2.1角色定义

在线审稿投稿管理系统

计算机工程学院数据库课程设计报告 设计名称：某期刊的在线投稿审稿管理系统 姓名：韩吉学号： 2015123352 专业班级：软嵌151 系（院）：计算机工程学院 设计时间：2017.11.20~~2017.12.1 设计地点：软件实验室

三、课程设计说明书 1、概述 1.1课题的来源及意义 从某网站编辑部的实际需求出发，编辑部面临着人员少，事务繁多，工作量大等问题，而现在的以手工为主的落后的管理方式加重了编辑人员的负担。这种状况，我们提出为该网站编辑部设计一个结构合理，适合编辑部工作需求的系统-期刊在线审核管理系统。该系统可以了作者在线投稿，专家在线审稿，编辑部在线审理稿件等全过程的网络化，比传统模式更加灵活方便。 1.2国内外发展状况 对于这方面，国内外发展的都较为成熟，格式各样的系统层出不穷，版权也不敬相同。 1.3课题的研究目标和内容 编写一个简单的系统，能够实现要求，为要求方解决暂时的燃眉之急。 1.4课题研究的方法手段 Java:编写图形界面----myeclipse10 链接数据库-- sqljdbc4.Jar 数据库:编写数据库---sql server 2012 图:画E-R图、数据流图---- visio 2016 2、需求分析 2.1 系统开发目标 开发一个简易的在线投稿管理系统。 2.2系统需求 （1）业务需求 网站的原在线投稿管理系统存在缺陷，需要重新编写系统。包括投稿人，审稿人，管理员，样稿的各自详细信息。 （2）用户需求 在线投稿审稿管理系统最终用户为投稿人、审稿人和杂志社管理员，有效地解决了传统模式下投递和送审的各种弊端，实现了作者的投稿、信息查询、信息反馈的便捷处理和编辑部规范高效化办公，从而节省了稿件处理的时间和流通费用，提高了稿件投递和投审的效率和安全性，同时也保证了杂志社所有的编辑能够在相同的业务平台进行业务处理，适应了集中管理的需要。通过规范流程、强化内部管理，建立强大的数据库，为数据分析、人员管理等提供强大的支持，为用户、编辑提供了安全的权限设置，使稿件分级处理，避免了处理流程的混乱，减低工作量、减少重复劳动，得出用户的下列实际要求： 2.2.2.1基本功能需求

SpringerLink数据库及其检索

欢迎来到零点花园 免费文献文献互助学术交流专业资源文献检索文献代理〖文献检索教程之〗 SpringerLink 作者：bhyt 整理：bhyt 零点?精品 荣誉出品 2007年4月25日

SpringerLink全文数据库及其检索 德国施普林格（Springer-Verlag）是世界上著名的科技出版公司，通过SpringerLink系统提供学术期刊及电子图书的在线服务，目前S pringer Link全文期刊已在我校开通，可在线阅读400多种电子全文期刊。包含学科如下：化学、计算机科学、经济学、工程学、环境科学、地球科学、法律、生命科学、数学、医学、物理与天文学等11个学科，其中许多为核心期刊。（一）登陆方式： 1、登陆之前，首先下载并安装Adob e公司的Acrobat Reader5.0以上浏览器。 2、登录到SpringerLink主页 https://www.wendangku.net/doc/dd13440665.html, （二）主页页面简介： SpringerLink主页面上方有几个按钮，其意义如下图所示：

（三）检索途径： s earch（检索）、 browse（浏览）二者的区别： search具有检索功能（可输入检索词）；browse仅具有浏览功能，不能输入检索词检索，只能浏览查找。 1、search的三种检索方法介绍。点击主页上的“高级检索按钮”(aadvanced search)，则如下图所示： articles by citation（按照引文检索文章），直接输入引文检索词检索文献； articles by text(根据全文检索文章)，直接输入全文检索词检索文献； publications（检索期刊），直接输入检索词检索

期刊在线投稿审稿管理系统需求规格说明书

期刊在线投稿审稿管理系统需求规格说明书． 期刊在线投稿审稿管理系统需求规格说明书 学生姓名：xx 学生学号：xxxxxx 所在班级：

12级计科 一、概述 1.1系统简介 数字化出版时代的到来，读者获取信息的维度不断拓宽，传统的投稿审稿模式已不能满足用户需求，也不能为期刊社或文学类网站

赢得竞争优势。 此时，采用在线方式完成网上稿件征集、投稿、校稿、审稿，除了可以加快稿件处理的速度，还可以使整个流程公开化、公正化、透明化，方便了现实用户。 1.2用户简介 （1）投稿人：知名作家或文学爱好者（已注册） （2）审稿人：知名报社编辑、知名作家或网站编辑（已注册） （3）普通用户：已注册并登录网民 （4）游客：未登录网民 （5）系统管理员：网站技术工作人员（已注册） 1.3项目的要求和目标 要求： ）描述项目的业务信息1（． （2）分析项目的管理工作的要求 （3）列出实体、联系 （4）指出实体和联系的属性

（5）画出E-R图 （6）画出层次方框图 （7）创建数据流程图 （8）建立数据字典 目标： （1）实现普通用户、投稿人、审稿人的信

息管理 （2）实现稿件类型、稿件信息的管理 （3）实现稿件的审阅过程管理 （4）创建存储过程，统计指定作者的稿件信息 （5）创建规则，使得作者的E-Mail必须满足电子邮件的基本格式 （6）建立数据库相关表之间的参照完整性约束。 1.4术语定义 数据字典：数据字典是指对数据的数据项、数据结构、数据流、数据存储、处理逻辑、外部实体等进行定义和描述，其目的是对数据流程图中的各个元素做出详细的说明。(Entity 联系图-图也称实体E-R图：E-R．

Springer-Link全文数据库及其特色服务功能介绍

Springer-Link 全文数据库及其特色服务功能介绍 ---科学研究的重要信息资源 全球首屈一指的科技及医学出版集团施普林格推出的Springer-Link 电子期刊全文库，内含1,200种经专家审稿（peer review）的学术期刊（其中许多为核心期刊），2500册在线系列丛书，还有不断扩充的内容，如陆续加入的在线参考工具书、在线电子图书及在线回溯数据库，按学科分为13个“在线图书馆(Online Libraries)”。与我校学科相关的有：化学及材料科学、计算机科学、商业及经济学、工程科学、地球及环境科学、数学、物理学、人文、社会科学及法律、建筑、设计及艺术等。 Springer Link 的特色及优点： 一、Springer 的个性化服务：速报提醒服务（Alerts）、个人爱好定制（Favorites） Alerts、 Favorites 是Springer 为用户提供的个性化服务，免费且方便，任何人可按喜好设定作者、学科或关键词，即可收到有关刊物的出版信息或可快速显示所选期刊的刊名及内容。 使用方法如下（注：在使用之前，用户需先到Springer Link 主页面进行登记注册Register）： 1、 在Springer-Link 主页面菜单栏中点击Alert ，显示两种类型table of contents Alerts 和keyword Alert ，读者可自行选择按内容或 关键词设定（如图1）、选择兴趣期刊，即可根据用户选择按e-mail 或Login 登入Springer Link 获得兴趣刊物的出版信息。 2、 在Springer-Link 主页面菜单栏中点击Favorites ，进入选择界面，选择、设定兴趣刊物（如图2），即可在主页面显示所选期刊 的刊名，点击则可快速显示其内容。（注：如若用户想改变设定，需先Log off，然后再Log in 重新设定即可。） 目录速报 关键词速报 图1 图2 二、在线优先出版Online First TM 这是一项革新的研究论文出版方式，让用户在印刷版发行前就能阅览经专家审稿的文章。经由数字对象辨别码（DOI ），方便

科技期刊在线投稿及审稿系统

随着多年以来计算机网络技术的发展普及，网络已然逐渐成为我们获取信息和文化资源的主要方法。在过去的二十年来，互联网技术已经被应用于各个领域，成为当今应用中使用最广泛，最具影响力的技术之一。设计科技期刊在线投稿及审稿系统可以方便地管理稿件的信息。本文将介绍科技期刊在线投稿及审稿系统的设计方案与实现过程。 科技期刊在线投稿和审稿系统分为前端系统和后端数据库两个部分。后端数据库主要包括：一般用户信息，专家信息，稿件的信息，基本费用的信息，编辑，首席信息和评级信息。前端系统模块有三种不同类型的用户：作者、专家、主编。作者首次使用系统需要注册一个账号，通过成功注册的该账号登录系统后才能进行修改个人密码、上传个人稿件和管理个人已上传的稿件等操作。专家登录系统后可以修改注册时填写的个人信息以及对稿件进行审核，并可以对该稿件给出审核意见。主编登录系统后可以修个自己的登录密码以及对注册用户信息、专家信息、稿件信息、稿费信息进行管理。 科技期刊在线投稿及审稿系统的开发对提升期刊专家和主编工作的效率和工作的质量有着重要的意义。充分利用计网（计算机网络）功能，可以实现投稿及审稿工作的全程非人工管理，将作者、审稿专家和主编从繁琐的手工书写、邮寄、批改，返回结果操作中释放出来，使投、审稿工作更加规范化和现代化。 关键词：期刊在线投稿及审稿系统；JSP技术；MySQL数据库管理系统；Tomcat应用服务器

Over the years, With the development and popularization of computer technology and the Internet,the network has gradually become the main way for us to obtain information and cultural resources. In the past two decades, Internet technology has been used in various fields, and has become one of the most widely used and influential technologies in today's application. The online contribution and review system of sci-tech periodicals can easily manage the basic information of manuscripts. This paper will introduce the design and implementation process of the system. The online contribution and evaluation system of sci-tech periodicals is divided into two parts: front-end system and back-end database system. The back-end database mainly includes: general user information, expert information, manuscript information, basic cost information, editing, chief information and rating information. There are three different types of users in the front-end system module: author, expert, editor-in-chief. For the first time, the author needs to register an account through the successfully registered account before he can modify his personal password, upload personal manuscripts and manage personal uploaded manuscripts. After experts log on to the system, they can modify their personal information and review their manuscripts. Give the audit opinion. After the editor-in-chief logs in the system, he can fix his own login password and manage the registered user information, expert information, manuscript information and manuscript fee information. The development of online contribution and review system of sci-tech periodicals based on JSP is of great significance to improve the efficiency and quality of periodical editing. Making full use of the computer network function (hereinafter referred to as the network function) can realize the non-manual management of the whole process of contribution and review, and release the author, the reviewer and the editor-in-chief from the tedious manual operation. Make the submission and examination work more standardized and modern. Key words:Online Journal Submission and Review System;MySQL Database Management System；Tomcat

外文数据库 Springer Link 斯普林格搜索技巧

Springer Link 检索指南 一、数据库介绍： Springer公司提供Springer LINK电子期刊服务。 目前Springer LINK所提供的全文电子期刊共包含400种学术期刊，按学科分为以下11个“在线图书馆”：生命科学、医学、数学、化学、计算机科学、经济、法律、工程学、环境科学、地球科学、物理学与天文学，是科研人员的重要信息源。 访问方式： 镜像服务器，访问地址：https://www.wendangku.net/doc/dd13440665.html,，访问权限控制：IP地址。 德国施普林格网址：https://www.wendangku.net/doc/dd13440665.html, 二、检索方法： 1. 主页： Springer中国镜像站：打开主页后，可以在其中选择使用方式或学科分类直接查找期刊。主页上还显示了登录信息和系统检测到的使用者的IP地址。当遇到问题需要帮助时，这些信息有助于我们的客户服务人员和技术人员确定问题所在。 德国Springer网址：打开主页后，点击Register后, 需要姓名、Email、用户名、密码等信息免费注册，注册完成后，系统显示用户名和密码，再次进入时，使用该用户名和密码点击Login进入系统。 2. 检索 2.1 文章检索 2.1.1 关键词检索 点击Search 进入检索界面，在“Search For”后的文字输入框输入关键词。 ★“Using”选项：在其后框内选择检索词间关系，当选择“Boolean Search”时，检索者可以在关键词之间输入逻辑运算符，输入“AND”表示逻辑与、输入“OR”表示逻辑“或”、输入“NOT”表示逻辑“非”，若不输入逻辑运算符，默认的逻辑运算关系为“与”－AND；当选择“All Words”时，检索全部关键词；当选择“Any Words”时，检索任意一个或多个关键词；当选择“Exact Phrase”时，全部输入的内容按词组进行精确查找。 ★“*”截词符——前方一致：用于关键词的末尾，以代替多个字符。

我的论文-基于Web在线投稿与稿件处理系统

石家庄铁道大学毕业设计 基于WEB的在线投稿与稿件处理系统 设计与实现 WEB-based Online Submission and Manuscript Handling System Design and Implementation 2011届信息科学与技术学院 专业计算机科学与技术 学号 20072401 学生姓名陈敏玮 指导教师封筠 完成日期 2011年6月1 日

毕业设计成绩单 学生姓名陈敏玮学号20072401 班级信0701-2 专业计算机科学与技术毕业设计题目基于WEB的在线投稿和稿件处理系统设计与实现 指导教师姓名封筠 指导教师职称教授 评定成绩 指导教师得分 评阅人得分 答辩小 组组长得分 成绩： 院长签字： 年月日

毕业设计任务书 题目基于WEB的在线投稿和稿件处理系统设计与实现 学生姓名陈敏玮学号20072401 班级信0701-2 专业计算机科学与技术 承担指导任务单位信息科学与技术学院 计算机系 导师 姓名 封筠 导师 职称 教授 一、设计内容 网络化的在线投稿和稿件处理系统，可克服传统的手工稿件处理的缺陷，具有工作效率高，节省人力、物力与财力，以及更高的安全性等优点。本课题旨在文献资料查阅与业务流程调研的基础上，把握投稿和稿件处理系统的国内外现状，明确本课题研究的目的和意义，设计并实现一个基于WEB的在线投稿和稿件处理。主要模块包括：用户权限划分与管理，信息管理与发布，作者注册与投稿、稿件管理、各种费用管理、编辑初审、专家审稿、定稿，数据维护等。 二、基本要求 要求陈敏玮同学独立完成整个系统的需求分析、详细设计和编码、调试，应按时完成进度要求。所设计开发的系统能达到实用。 要求论文正文不少于1.5万字，外文翻译3000~5000字，计算机应用300机时以上，提供软件设计说明文档、源程序。1 三、主要技术指标 设计合理，符合相关规范；用户界面美观，规范；响应速度快，操作便捷；系统完善，便于维护和扩展。 四、应收集的资料及参考文献 [1] 浏览、分析计算机类中文核心期刊与重要会议网站，熟悉在线投稿和稿件处理流程 [2] 搜集与网络化稿件处理系统相关的参考文献资料 [3] 动态网页制作技术相关书籍 [4] SQL SERVER相关书籍 [5] 系统设计与计算机软件开发相关书籍 五、进度计划 第1周- 第6周毕业实习；查阅资料，需求调研，撰写开题报告；熟悉环境及工具。 第7周- 第10周掌握相关理论与方法；需求分析、概要设计、详细设计。 第11周- 第14周系统开发、编码实现、系统调试。 第15周- 第16周撰写论文并准备答辩。 教研组主任签字时间年月日

在线审稿投稿管理系统课程设计报告资料

课程设计报告 (2015-- 2016年度第1学期) 实验名称：数据库应用课程设计题目：在线投稿审稿管理系统院系：控制与计算机工程学院班级：计算1302 学号：1131220207 学生姓名：兰鑫玥 指导教师：周长玉 设计周数： 1 周 成绩： 日期：2016年1月17日

一、课程设计的目的与要求 目的 1.学习和实践在分析和设计计算机应用系统所需要的知识，包括面向对象的系统分析与设计，对数据库 做进一步的了解，掌握相关知识； 2.进一步加强对数据库运用能力和熟练掌握数据库中的重要知识，了解如何从数据库中读写有关数据； 3.培养分析问题、解决问题的能力。 要求 1.完成数据库系统的安装与设置。 2.根据具体的课题完成需求分析。 3.完成数据库应用系统的逻辑设计。 4.创建数据库、数据表。 5.完成设计报告。 二、设计正文 1.需求分析 1.1 调查用户需求 在线投稿审稿管理系统最终用户为投稿人、审稿人和杂志社管理员，有效地解决了传统模式下投递和送审的各种弊端，实现了作者的投稿、信息查询、信息反馈的便捷处理和编辑部规范高效化办公，从而节省了稿件处理的时间和流通费用，提高了稿件投递和投审的效率和安全性，同时也保证了杂志社所有的编辑能够在相同的业务平台进行业务处理，适应了集中管理的需要。通过规范流程、强化内部管理，建立强大的数据库，为数据分析、人员管理等提供强大的支持，为用户、编辑提供了安全的权限设置，使稿件分级处理，避免了处理流程的混乱，减低工作量、减少重复劳动，得出用户的下列实际要求： 1.1.1基本功能需求 出版社的在线投稿审稿管理系统包含以下几方面信息： ?投稿人的基本信息 每个投稿人都有唯一的编号，有真实姓名，有笔名，有联系方式包括：电话号码、联系地址、Email 等。 ?审稿人的基本信息 审稿人负责审理投稿人的稿件且为管理员管理添加或删除，每个审稿人都有唯一的编号，有真实姓名，有联系电话。 ?管理员的基本信息 管理员负责管理审稿人，统计稿件信息，指定审稿人去审理指定的稿件，每个管理员都有唯一的编号，有姓名，有联系电话。

SPRINGER数据库及检索方法介绍

SPRINGER数据库及检索方法介绍 一、数据库简介 Springer是世界著名的科技出版公司，通过Springer LINK系统提供电子期刊和电子图书的在线服务，目前Kluwer出版社已被Springer合并，Kluwer的电子期刊也被收录在Springer LINK系统中。Springer LINK收录电子期刊1300多种，电子图书24200多种。我校订购了其中的2005-2009版权年电子图书（包括图书、丛书、参考工具书）。另外国家科技图书文献中心(NSTL)为全国用户订购了Springer的回溯库，包括960多种期刊和14种丛书，这些期刊和丛书都回溯至第1卷第1期。 具体学科涉及：数学、物理与天文学、化学、生命科学、医学、工程学、计算机科学、环境科学、地球科学、经济学、法律。 二、检索指南 1. 登录 正常进入数据库后，会在左上角显示欢迎，页面的右上部可以选择界面的语言，可供选择的语言有中文简体，中文繁体，英语，德语，韩语。 2. 浏览 在主界面上，Springer提供了分别按内容类型（期刊、图书、丛书等）、学科和特色图书馆进行浏览。每种分类后都有一个数字标记种类的个数。在浏览页面的右侧，可以按出版物名称的起始字母检索或浏览，或按出版年、语言、学科等分类浏览。 内容类型 所有内容类型 (4,663,528) 出版物 (40,268) 期刊 (2,235) 丛书 (1,097) 图书 (36,936) 参考工具书 (164) Protocols (20,273) 特色图书馆

中国在线科学图书馆 (69,181) 俄罗斯在线科学图书馆 (521,871) 进入任一分类以后可以浏览。注意：刊名或书名前有表示可阅读所有全文，表示可阅读部分全文，表示不能阅读全文。 3、检索文章 在右边的Find对话框可以进行检索，点击省略号按钮可以打开组配符号，按Bool运算符组配你的检索式。。点击more options可以到达检索界面。可供组配的字段为All text、Title、Summary、Author、Editor、ISSN、ISBN、DOI。同时可以限定年限，以及对输出结果按相关度或时间进行排序。点击检索结果的题名可以看到文章摘要，点击pdf图标可以下载全文。在导航栏中点击Search，可以到达检索页面。 4、结果处理 检索词在检索结果中会高亮显示，点击“Disablehighlighting”可以清除高亮，点击“PDF”按钮可以下载全文。在检索结果界面右侧可以按学科和作者进行对结果进行精炼。点击文献名后，右下角可以将题录导出为RIS或文本格式。 检索结果界面的右侧有一系列图标，可下载所有结果列表，并按不同格式导出，或者RSS 订阅。 题名点击“Add to marked items”，可以将论文添加到标记列表，稍后可在导航栏中“My menu marked items”中找到该列表。 5、个性化服务 在首页左侧的欢迎界面下，有一个用户注册的按钮“please log in or register”，注册为Springer的个人用户可以使用个性化服务。 点击检索界面的磁盘按钮，可以选择检索历史保存、email、导入RSS阅读器或定制一个Alert，以便可以定时在Email中收到该检索的更新结果。 注册用户的功能： （1）查看订阅刊物 您所有的订阅刊物将被列在这里。请注意这里列出的订阅刊物不包括您所属机构的订阅刊物。关于您所属机构的详情，请选择左上角的认同名单。

在线投稿审稿系统代码

主页登录系统的设计： 页面： <%@ page contentType="text/html" pageEncoding="gb2312"%>