基于形状匹配的商标图像检索技术研究
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摘要
随着市场经济的发展,商标数量逐年递增。传统的基于分类、文本标注的商标图像检索方法存在着很大的难题,包括手工分类/注解工作量大、描述主观性、描述不全面性等问题。基于内容的图像检索技术可以克服这些弊端,它在商标检索领域得到了非常广泛的应用。
基于内容的商标图像检索方法利用图像自身包含的特征属性,如颜色、形状、纹理及空间位置关系等建立图像的索引,然后利用这些特征进行检索。作为人工图像的商标图像,其形状特征较其它特征更为显著,人们往往更多地通过形状来识别不同的商标。本文主要针对基于形状匹配的商标图像检索关键问题展开研究,包括:商标图像分割技术、形状边界描述方法、形状区域描述方法、形状特征融合及匹配技术、基于多特征融合的子图像检索方法等,文中提出了一些解决问题的方法,具有一定的理论意义和实际应用价值。本文的主要工作和贡献如下:
1.深入研究了商标图像分割技术,提出了一个基于分水岭和高斯重叠率衡量多层融合的商标图像分割新方法WG-OLR;该方法可高效对商标图像进行自动分割;
2.研究基于边界的商标形状特征匹配方法,提出了一个基于角点检测及其Delaunay图的形状边界特征匹配方法DT-MATCH;该方法可快速的对非复杂的商标形状进行描述,并具有较好的检索效率;
3.研究基于区域的商标形状特征匹配方法,针对一类基于分区块统计的形状描述方法进行比较研究,确定了基于分区块统计描述思想下最适合的形状描述方法CAM;
4.分析了基于边界和基于区域特征形状描述方法的优缺点,并将这两种特征进行融合,针对商标的形状,提出了一种融合边界和区域特征的全图商标图像检索方法BR-MATCH;该方法不仅具有较好的匹配效果,同时具有较快的检索速度;
5.利用建立的商标图像分割技术和形状描述方法,同时融合颜色、空间位置关系等其它特征,提出了一种基于多特征融合的子图商标图像检索方法SBR-MATCH;子图检索方法较全图检索方法精度有了进一步的提高。
With the development of market economy, the quantity of trademark increases progressively year by year. The tradition trademark image retrieval based on classified or text labeling has many problems, including the very load of manual illustration work, subjectivity, inaccuracy, etc. Content-based image retrieval (CBIR) technology can overcome these problems, so it obtained the very widespread application in the trademark retrieval domain.
The methods of CBIR retrieve the images using the characteristics of themselves, such as color, shape, texture and the space position relations. Trademark image as an artificial image, compared with other features, shape is the most remarkable, so we always use the shape feature to distinguish various trademarks This dissertation focuses on the key technologies of the shape matching based trademark image retrieval, including: trademark image segmentation technology, boundary-based shape description method, region-based shape description method, shape feature fusion and matching, sub-image multi-characteristic fusion retrieval, etc. The main contributions of this dissertation can be summarized as follows:
1. Several key technologies of trademark image segmentation are deeply investigated and analyzed. A new multi-layer fusion image segmentation method is proposed, named WG-OLR. This method can carry on the automatic image segmentation with high efficiency.
2. Research on the boundary-based shape description method of the trademark image. A new shape boundary matching method based on comer detection and Delaunay Triangulation Net, named DT-MATCH, is proposed. This method can carry on fast feature description to the non-complex shape and has the good retrieval efficiency.
3. Research on the region-based shape description method of the trademark image. We mainly aim at one kind of sub-area statistics shape description method to carry on quite studies and find out the most suitable shape description method based on the sub-area statistics description thought.
4. After analyzing the advantages and disadvantages of the boundary-based and region-based shape description method, in view of the trademark shape, we propose a new total-graph trademark image retrieval method that fuses the boundary and the region features, named BR-MATCH. This method not only has the good match effect, simultaneously has the quick retrieval speed.
5. Using the established image segmentation technology, synthesizing to the research on shape description method, simultaneously fusing the color, the space position relations and other characteristics, we propose a new sub-graph trademark image retrieval method based on the multi-characteristic fusion, named SBR-MATCH. Compares with the total-graph retrieval method, the precision of sub-graph retrieval method has the further enhancement.
基于内容的商标图像检索方法利用图像自身包含的特征属性,如颜色、形状、纹理及空间位置关系等建立图像的索引,然后利用这些特征进行检索。作为人工图像的商标图像,其形状特征较其它特征更为显著,人们往往更多地通过形状来识别不同的商标。本文主要针对基于形状匹配的商标图像检索关键问题展开研究,包括:商标图像分割技术、形状边界描述方法、形状区域描述方法、形状特征融合及匹配技术、基于多特征融合的子图像检索方法等,文中提出了一些解决问题的方法,具有一定的理论意义和实际应用价值。本文的主要工作和贡献如下:
1.深入研究了商标图像分割技术,提出了一个基于分水岭和高斯重叠率衡量多层融合的商标图像分割新方法WG-OLR;该方法可高效对商标图像进行自动分割;
2.研究基于边界的商标形状特征匹配方法,提出了一个基于角点检测及其Delaunay图的形状边界特征匹配方法DT-MATCH;该方法可快速的对非复杂的商标形状进行描述,并具有较好的检索效率;
3.研究基于区域的商标形状特征匹配方法,针对一类基于分区块统计的形状描述方法进行比较研究,确定了基于分区块统计描述思想下最适合的形状描述方法CAM;
4.分析了基于边界和基于区域特征形状描述方法的优缺点,并将这两种特征进行融合,针对商标的形状,提出了一种融合边界和区域特征的全图商标图像检索方法BR-MATCH;该方法不仅具有较好的匹配效果,同时具有较快的检索速度;
5.利用建立的商标图像分割技术和形状描述方法,同时融合颜色、空间位置关系等其它特征,提出了一种基于多特征融合的子图商标图像检索方法SBR-MATCH;子图检索方法较全图检索方法精度有了进一步的提高。
With the development of market economy, the quantity of trademark increases progressively year by year. The tradition trademark image retrieval based on classified or text labeling has many problems, including the very load of manual illustration work, subjectivity, inaccuracy, etc. Content-based image retrieval (CBIR) technology can overcome these problems, so it obtained the very widespread application in the trademark retrieval domain.
The methods of CBIR retrieve the images using the characteristics of themselves, such as color, shape, texture and the space position relations. Trademark image as an artificial image, compared with other features, shape is the most remarkable, so we always use the shape feature to distinguish various trademarks This dissertation focuses on the key technologies of the shape matching based trademark image retrieval, including: trademark image segmentation technology, boundary-based shape description method, region-based shape description method, shape feature fusion and matching, sub-image multi-characteristic fusion retrieval, etc. The main contributions of this dissertation can be summarized as follows:
1. Several key technologies of trademark image segmentation are deeply investigated and analyzed. A new multi-layer fusion image segmentation method is proposed, named WG-OLR. This method can carry on the automatic image segmentation with high efficiency.
2. Research on the boundary-based shape description method of the trademark image. A new shape boundary matching method based on comer detection and Delaunay Triangulation Net, named DT-MATCH, is proposed. This method can carry on fast feature description to the non-complex shape and has the good retrieval efficiency.
3. Research on the region-based shape description method of the trademark image. We mainly aim at one kind of sub-area statistics shape description method to carry on quite studies and find out the most suitable shape description method based on the sub-area statistics description thought.
4. After analyzing the advantages and disadvantages of the boundary-based and region-based shape description method, in view of the trademark shape, we propose a new total-graph trademark image retrieval method that fuses the boundary and the region features, named BR-MATCH. This method not only has the good match effect, simultaneously has the quick retrieval speed.
5. Using the established image segmentation technology, synthesizing to the research on shape description method, simultaneously fusing the color, the space position relations and other characteristics, we propose a new sub-graph trademark image retrieval method based on the multi-characteristic fusion, named SBR-MATCH. Compares with the total-graph retrieval method, the precision of sub-graph retrieval method has the further enhancement.
引文
[1]中国商标网.http://www.ctmo.gov.cn/.
[2]中华人民共和国国家工商行政管理总局.http://www.saic.gov.cn/.
[3]中华人民共和国国家知识产权局.http://www.sipo.gov.cn/sipo/.
[4]世界知识产权组织.http://www.wipo.int/portal/index.html.zh.
[5]中国知识产权在线.http://www.ipsoon.org/.
[6]中国商标专网(白兔商标查询).http://www.cha-tm.com/.
[7]德龙中国商标查询库.http://www.dltm.net/.
[8]北京商标网.http://www.pekingtm.cn/Articlc/2812.html.
[9]郭丽.基于内容的商标图像检索研究[D].南京理工大学博士学位论文,2003.
[10]中国商标数据库.http://www.86tm.com/.
[11]章毓晋.基于内容的视觉信息检索[M].北京:科学出版社,2003.
[12]J.P.Eakins,K.J.Riley,J.D.Edwards."Shape feature matching for trademark image retricval"[J].Image and Video Retrieval,Proceedings,2003,2728:28-38.
[13]Y.Huang,L.Guo."Binary trademark retrieval based on sub-block image"[J].Nanjing Hangkong Hangtian Daxue Xuebao/Journal of Nanjing University of Aeronautics and Astronautics,2006,38(6):737-742.
[14]B.J.Zou,Y.Yao,L.Zhang."A new algorithm for trademark image retrieval based on sub-block of polar coordinates"[C].Shanghai,China,Springer Verlag,Heidelberg;D-69121,Germany,2007,4740 NCS:91-97.
[15]章毓晋.图像工程(上册)-图像处理和分析[M].北京:科学出版社,1999.
[16]C.Shahabi,M.Safar."An experimental study of alternative shape-based image retrieval techniques"[J].Multimedia Tools and Applications,2007,32(1):29-48.
[17]N.Wei,M.E.Celebi,G.H.Geng."Content Based Retrieval and Classification of Cultural Relic Images"[C].Advances in Neural Networks-Isnn 2005:Second International Symposium on Neural Networks,Part 2,Proceedings,2005:292-298.
[18]章毓晋.图像理解与计算机视觉[M].北京:电子工业出版社,2000.
[19]R.C.Veltkamp,L.J.Latecki."Properties and Performance of Shape Similarity Measures"[C].10th IFCS Conf.Data Science and Classification,Slovenia,2006.
[20]M.Bober."MPEG-7 visual shape descriptors"[J].IEEE Transactions on Circuits and Systems for Video Technology,2001,11(6):716-719.
[21]L S.Hsieh,K.C.Fan."Multiple classifiers for color flag and trademark image retrieval"[J].IEEE Transactions on Image Processing,2001,10(6):938-950.
[22]B.Verma,M.Blumenstein,M.Ghosh."A novel approach for structural feature extraction:Contour vs.direction"[J].Pattern Recognition Letters,2004,25(9):975-988.
[23]P.Y.Yin,C.C.Yeh."Content-based retrieval from trademark databases"[J].Pattern Recognition Letters,2002,23(1-3):113-126.
[24]C.C.Waag,L.H.Chen."Content-based color trademark retrieval system using hit statistic"[J].International Journal of Pattern Recognition and Artificial Intelligence,2002,10(5):603-619.
[25]H.L.Peng,S.Y.Chen."Trademark shape recognition using closed contours"[J].Pattern Recognition Letters,1997,18(8):791-803.
[26]M.T.Chang,S.Y.Chen."Deformed trademark retrieval based on 2D pseudo-bidden Markov model"[J].Pattern Recognition,2001,34(5):953-967.
[27]M.S.Kankanhalli,B.M.Mehtre,H.Y.Huang."Color and spatial feature for content-based image retrieval"[J].Pattern Recognition Letters,1999,20(1):109-118.
[28]J.L.Shih,L.H.Chen."A new system for trademark segmentation and retrievar"[J].Image and Vision Computing,2001,19(13):1011-1018.
[29]G.Cortelazzo,et al."Trademark shapes description by string-matching techniques"[J].Pattern Recognition,1994,27(8):1005-1018.
[30]A.K Jain,A.Vailaya."Image Retrieval using Color and Shape"[J].Pattern Recognition,1996,29(8):1233-1244.
[31]C.H.Teh,R.H.Chin."On Image Analysis by the Method of Moments"[J].IEEE Trans.PAMI,1988,10(4):496-513.
[32]W.Y,Kim,Y.S.Kim."A region-based shape descriptor using Zernike moments"[J].Signal Processing-Image Communication,2000,16(1-2):95-102.
[33]S.D.Lin,et al."Trademark image retrieval by distance-angle pair-wise histogram"[J].International Journal of Imaging Systems and Technology,2005,15(2):103-113.
[34]姚玉荣,章毓晋.”利用小波和矩进行基于形状的图像检索”[J].中国图像图形学报,2000,5(3):206-210.
[35]J.P.Eakins,J.M.Boardman,M.E.Graham."Similarity retrieval of trademark image"[J].IEEE Multimedia,1998,5(2):53-63.
[36]M.Flickner."Query By Image and Video Content:The QBIC System"[J].IEEE Computers,1995.
[37]virage 公司.http://www.virage.com.
[38]Excalibur 技术公司.http://vrw.excalib.com.
[39]A.Pentland,R.W.Pioard,S.Solaroff."Photobook:Content-based Manipulation of Image Databases"[J].Internal Journal of Computer Vision,1996:34-47.
[40]T.P.Minks,R.W.Picard."Interactive learning with a society of models"[J].Pattern Recognition,1997,30(4):565-581.
[41]Visual SEEk.http://www.ctr.columbia.edu/VisualSEEK/.
[42]S.D.Servetto,et al."A region-based representation of images in MARS"[J].Journal of Vlsi Signal Processing Systems for Signal Image and Video Technology,1998,10(1-1):137-150.
[43]M.Ortega,et al."Supporting ranked Boolean similarity queries in MARS"[J].Ieee Transactions on Knowledge and Data Engineering,1998,10(6):905-925.
[44]M.Ortega-Binderberger,S.Mehrotra."Relevance feedback techniques in the MARS image retrieval system"[J].Multimedia Systems,2004,9(6):535-547.
[45]NETRA.http://maya.ece.ucsb.edu/Netra.
[46]C.Carson,et al."Blobworld:Image segmentation using expectation-maximization and its application to image querying"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,24(8):1026-1038.
[47]J.Li,J.Z.Wang."Automatic linguisfic indexing of pictures by a statistical modeling approach"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2003,25(9):1075-1088.
[48]I.J.Cox,et al."The Bayesian image retrieval system,PicHunter:Theory,implementation,and psychophysical experiments(vol 9,pg 20,2000)"[J].IEEE Transactions on Image Processing,2000,9(3):524-524.
[49]ImageRover.http://www.es.bu.edu/groups/ive/Imagerover.
[50]Surfimage.http://www.rocq.inria.fr/imedia.
[51]PICSearch.http://www.cs.helsinki.fi/～klemstro/picsearch.
[52]PicToSeek.http://zomax.wins.uva.nl:5345/zomax/html/zomax.html.
[53]M.Kokare,B.N.Chatterji,P.K.Biswas."A survey on current content based image retrieval methods"[J].Iete Journal of Research,2002,48(3-4):261-271.
[54]Han,Guo."A new image retrieval model supporting query by semantics and example"[C].IEEE Conference on Image Processing,2002.
[55]H.Jin,R.H.He,W.B.Tao."Exploring semantic association rules between keyword and visual feature clusters for web image retrieval"[J].Chinese Journal of Electronics,2008,17(1):59-65.
[56]X.Q.Zhu,et al."New query refinement and semantics integrated image retrieval system with semiautomatic annotation scheme"[J].Journal of Electronic Imaging,2001,10(4):850-860.
[57]S.Manjunath,et al."Color and Texture Descriptors"[J].IEEE Trans.on Circuit and Systems for Video Technology,2001.
[58]M.Ferecatu,N.Boujemaa,M.Crucianu."Semantic interactive image retrieval combining visual and conceptual content descripfion"[J].Multimedia Systems,2008,13(5-6):309-322.
[59]J.K.Wu."Content-baaed indexing of multimedia databases"[J],Ieee Transactions on Knowledge and Data Engineering,1997,9(6):978-989.
[60]X.M.Zhon,C.H.Ang,T.W.Ling."Indexing for multipoint interactive similarity retrieval in iconic spatial image databases"[J].Journal of Visual Languages and Computing,2008,19(1):24-38.
[61]S.Aouat,et al."3D object indexing and recognition"[J].Applied Mathematics and Computation,2008,196(1):318-332.
[62]Q.Zhang,E.Izquierdo."Combining low-level features for semantic extraction in image retrieval"[J].Eurasip Journal on Advances in Signal Processing,2007.
[63]T.Qin,et al."An active feedback framework for image retrieval"[J].Pattern Recognition Letters,2008,29(5):637-646.
[64]P.C.Cheng,et al."A two-level relevance feedback mechanism for image retrieval"[J].Expert Systems with Applications,2008,34(3):2193-2200.
[65]G.P.Nguyon,M.Worring."Optimization of interactive visual-similarity-baaed search"[J].Acm Transactions on Multimedia Computing Communications and Applications,2008,4(1):1-23.
[66]C.Liu,et al."Automatic estimation and removal of noise from a single image"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2008,30(2):299-314.
[67]M.R.Hejazi,Y.S.Ho."An efficient approach to texture-based image retrieval"[J].International Journal of Imaging Systems and Technology,2007,17(5):295-302.
[68]S.Kiranyaz,M.Ferreira,M.Gabbonj."A genetic shape/texture descriptor over multiscale edge field:2-D walking ant histogram"[J].IEEE Transactions on Image Processing,2008,17(3):377-391.
[69]郑南宁.计算机视觉与模式识别[M].北京:国防工业出版社,1998.
[70]张爱华.基于模糊聚类分析的图像分割技术研究[D].华中科技大学博士学位论文,2004.
[71]Q.Chen,et al."A double-threshold image binarization method based on edge detector"[J].Pattern Recognition,2008,41(4):1254-1267.
[72]W.Doyle."Operations Useful for Similarity-invariant Pattern Recognition"[J].Journal of ACM,1962,9(2):259-267.
[73]N.Otsu."A threshold selection method from gray-level histogram"[J].IEEE Trans on System Man Cybemet,1979:62-66.
[74]T.Pun."A New Method for Gray-level Picture Thresholding Using The Entropy of Histogram"[J].Signal Processing,1980,2:223-237.
[75]M.Sonka,V.Hlavac,R.Boyle.Image Processing,Analysis,and Machine Vision(Second Edition)[M].北京:人民邮电出版社,2003.
[76]K.Hammonche,M.Dial,P.Siarry."A multilevel automatic thresholding method based on a genetic algorithm for a fast image segmentation"[J].Computer Vision and Image Understanding,2008,109(2):163-175.
[77]A.D.Brink."Thresholding Digital Images Using Two-dimensional Entropics"[J].Pattern Recognition,1992,25(8):803-808.
[78]O.Laligant,F.Truchetet,F.Meriandeau."Regularization preserving localization of close edges"[J].IEEE Signal Processing Letters,2007,14(3):185-188.
[79]L.Matalas,R.Benjamin,R.Kitney."An Edge Detection Technique Using the Facet Modal and Parameterized Relaxation Labeling"[J].IEEE Trans on Pattern Analysis and Machine Intelligence,1997,19(4):328-341.
[80]J.Canny."A Cmputational Approach to Edge Dctection"[J].IEEE Trans Pattern Analysis and Machine Intelligence,1986,8(6):679-698.
[81]尹平,王润生.”自适应多尺度边缘检测”[J].软件学报,2000,11(B):990-994.
[82]X.B.Wen,H.Zhang,Z.Tian."A multiscale serf-growing probabilistic decision-based neural network for segmentation of SAR imagery"[C].Pricai 2006:Trends in Artificial Intelligence,Proceedings,2006,4099:1166-1170.
[83]R.Legault,C.Y.Suen."Optimal local weighted averaging methods in contour smoothing"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1997,19(8):801-817.
[84]H.D.Cheng,Y.Sun."A hierarchical approach to color image segmentation using homogeneity"[J].IEEE Transactions on Image Processing,2000,9(12):2071-2082.
[85]Y.T.Wu,et al."A top-down region dividing apprnaoh for image segmentation"[J].Pattern Recognition,2008,41(6):1948-1960.
[86]L.Vincent,S.Pierre."Watersheds in Digital Spaces:An Efficient Algorithm Breed on Immersion Simulations"[J].IEEE Transactions of Pattern Analysis and Machine Intelligence,1991,13(6):583-598.
[87]杨文明.时空联合的视频对象分割[D].浙江大学博士学位论文,2006.
[88]李相镐,李洪兴,陈世权.模糊聚类分析及其应用[M].贵阳:贵州科学技术出版社,1994.
[89]I.Bloch,G.Martino,A.Petrosino."A fuzzy mathematical morphology approach to multiseeded image segmentation"[J].Fuzzy Logic and Applications,2006,3849:362-368.
[90]Y.Fang,C.Pan,L.Liu."On-line training of neural network for color image segmentation"[C].Advances in Natural Computation,Pt 2,Proceedings,2005,3611:135-138.
[91]Q.Sun,et al."A fully unsupervised image segmentation algorithm breed on wavelet-domain hidden Markov tree models"[C].Advanced Concepts for Intelligent Vision Systems,Proceedings,2005,3708:507-514.
[92]K.E.Melkemi,M.Batouche,S.Foufou."A multiagent system approach for image segmentation using genetic algorithms and extremal optimization heuristics"[J].Pattern Recognition Letters,2006,27(11):1230-1238.
[93][美]K.R.Castlcman著、朱志刚等译.数字图像处理[M].清华大学出版社,1999.
[94]胡小锋,赵辉编著.Visual C++/matlab图像处理与识别实用案例精选[M].北京:人民邮电出版社,2004年9月.
[95]M.K.Hu."Visual Pattern Recognition by Moment Invariants"[J].IRE Trans.Info Theory,1962,IT-8:179-187.
[96]M.Teague."Image analysis via the general theory of moments"[J].Journal Optical America,1980,70(8):920-930.
[97]陈晓飞.基于骨架的目标表示和识别技术研究[D].国防科学技术大学博士学位论文,2004.
[98]S.Santini,R.Jain."Similarity measures"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1999,21(9):871-883.
[99]Y.Rubner,C.Tomasi,L.J.Guibas."A metric for distributions with applications to image database"[C].In 6th International Conference on Computer Vision,Bombay,India.,1998:59-66.
[100]S.Cohen,L.Guibas."The Mover's Distance under Transformation Sets"[C].The 7th IEEE International Conference on Computer Vision,Corfu,Greece,1999:173-187.
[101]M.Sharon,L.Ting-Sheng,T.John."Evaluating a content based image retrieval aystem"[C].In the proceedings of the 24th annual international ACM SIGIR conference on research and development in information retrieval,New Orleans,Louisiana,United States,2001:232-240.
[102]孙兴华,杨静宇.”基于子图像多特征组合的商标图像检索”[J].模式识别与人工智能,2002,15(1):14-20.
[103]赵晨光,宋利伟,庄天戈.”基于分水岭区域差异性的多级图像分割”[J].上海交通大学学报,2004,38(9):1489-1491.
[104]崔明,孙守迁,潘云鹤.“基于改进快速分水岭变换的图像区域融合”[J].计算机辅助设计与图形学学报,2005,17(3):546-552.
[105]H.P.Ng,et al."Masseter segmentation using an improved watershed algorithm with unsupervised classification"[J].Computers in Biology and Medicine,2008,38(2):171-184.
[106]J.Cousty,et el."Fusion graphs:Merging properties and watersheds"[J].Journal of Mathematical Imaging and Vision,2008,30(1):87-104.
[107]R.Lotufo,W.Silva."Minimal set of markers for the watershed transform"[C],International Symposium on Mathematical Morphology,ISMM2002,Australia,2002:359-368.
[108]J.Park,J.M.Keller."Snakes on the watershed"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2001,23(10):1201-1205.
[109]龚剑.”一种基于分水岭和模糊聚类的多级图像分割算法”[J].第—军医大学学报,2004,24(3):32-33.
[110]Z.Hong,et el."Measuring Overlap-rate in Hierarchical Cluster Merging for Image Segmentation and Ship Detection"[C].Proceeding of the 4th International Conference on Fuzzy Systems and Knowledge Discovery,2007,4:420-424.
[111]洪志令,et al.“基于分水岭和重叠率衡量的多级彩色图像分割”[J].中国图象图形学学报,2008年出版.
[112]洪志令,姜青山,王声瑞.”基于重叠率衡量融合策略的层次聚类算法研究”[J].计算机研 究与发展,2007,44(Suppl.):117-122.
[113]Z.Hong,Q.Jiang,S.Wang."Measuring Overlap-Rate in a Hierarchical Approach for Color Image segmentation"[C].Proceeding of the 2nd International Conference on Innovative Computing,Information and Control,ICICIC,2007:442-446.
[114]International Color Consortium.www.color.org.
[115]S.Arora,et al."Multilevel thresholding for image segmentation through a fast statistical recursive algorithm"[J].Pattern Recognition Letters,2008,29(2):119-125.
[116]S.Wang,H.Sun."Measuring Overlap-Rate for Cluster Merging in a Hierarchical Approach to Color Image Segmentation"[J].International Journal of Fuzzy Systems,2004,6(3).
[117]D.Martin,et al."A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics"[C].ICCV,2001,2:416-423.
[118]D.R.Martin,C.C.Fowlkes,J.Malik."Learning to detect natural image boundaries using local brightuess,color,and texture cued'[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2004,26(5):530-549.
[119]卢汉清,et al.”基于内容的视频信号与图像库检索中的图像技术”[J].自动化学报,2001,27(1):56-69.
[120]黄元元,郭丽,杨靖宇.”基于形状与空间特征的二值商标图像检索”[J].模式识别与人工智能,2003 16(2):241-245.
[121]B.Luo,R.C.Wilson,E.R.Hancock."Spectral embedding of graphs"[J].Pattern Recognition,2003,36(10):2213-2230.
[122]T B.Sebastian,P.N.Klein,B.B.Kimia."Recognition of shapes by editing their shock graphs"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2004,26(5):550-571.
[123]H.F.Zhao,M.Kong,B.Luo."Shape representation based on polar-graph spectra"[J].Intelligent Computing in Signal Processing and Pattern Recognition,2006,345:900-905.
[124]N.M.Tahir,et al "Shook graph for repres entation and modeling of posture"[J].Etri Journal,2007,29(4):507-515.
[125]赵海峰.基于图的形状描述方法研究[D].安徽大学博士学位论文,2006.
[126]Z.Hong,Q.Jiang."Shape Image Retrieval based on Comer Delaunay Triangulation"[J].Journal of Computational Information Systems,2007,3(5):1861-1866.
[127]Z.Hong,Q.Jiang,X.Wei."Shape Representation and Similarity Measure Based on Delaunay Triangulation"[J].Journal of Cruangxi Normal University,2007,25(4):261-264.
[128]S.M.Smith,J.M.Brady."SUSAN-A new approach to low level image prooessing"[J].International Journal of Computer Vision,1997,23(1):45-78.
[129]H.X.C,Y.N.H.C."Curvature scale space corner detector with adaptive threshold and dynamic region of support"[C].Proc 17th International Conference on Pattern Recognition.Cambridge,UK,2004:791-794.
[130]H.Haron,S.M.Shamsuddia,D.Mohamed."A new corner detection algorithm for chain code representation"[J].International Journal of Computer Mathematics,2005,82(8):941-950.
[131]Freeman.H,Davis.L.S."A comer finding algorithm for chaincoded curves"[J].IEEE Transactions on Computers,1977,C26(3):297-303.
[132]H.Wang,C.S.Chug C.T.Sim."Real-time object tracking from corners"[J].Robotica,1998,16:109-116.
[133]C.Harris,M.Stephens."A combined corner and edge detector"[C].In Alvey Virion Conference,Cambridge,UK,1987:147-151.
[134]孟坛魁,华成英.”一种改进的灰度图像角点检测算法”[J].计算机应用研究,2005,4:105-106,129.
[135]F.Mokhtarian,R.Suomela."Robust image corner detection through curvature scale space"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1998,20(12):1376-1381.
[136]F.Mokhtarian,F.Mohanna."Enhancing the curvature scale space corner detector"[C].Prec.Scandinavian Conference on Image Analysis,Bergen,Norway,,2001:145-152.
[137]刘广海.基于纹理和形状特征的图像检索技术研究[D].南京理工大学硕士学位论文,2004.
[138]Y.Tao,W.I.Grosky."Delaunay triangulation for image object indexing:A novel method for shape representation"[C].In Proceedings of the Seventh SPIE Symposium on Storage and Retrieval for Image and Video Databases,1999:631-942.
[139]R.A.Dwyer."A Faster Divide-and-Conquer Algorithm for Constructing Delauaay Triangulations"[J].Algorithmic,1987,2(2):127-151.
[140]Zhou.D.X,Li.G.H,Liu.Y.H."Effective corner matching based on delaunay triangulation"[C].IEEE International Conference on Robotics and Automation,New Orleans,LA,USA,2004:2730-2735.
[141]E.R.van Dam,W.H.Haemers."Which graphs are determined by their spectrum?"[J].Linear Algebra and Its Applications,2003,373:241-272.
[142]范益政.图的谱理论[D].中国科学技术大学博士学位论文,2001.
[143]B.Xiao,H.Yu,E.Hancock."Graph matching using manifold embedding"[C].Image Analysis and Recognition,Pt 1,Proceedings,2004,3211:352-359.
[144]J.Han,M.Kamber.Data Mining:Conceptes and Techniques[M].China Machine Press,2006.
[145]G.J.Lu,A.Sajjanhar."Region-based shape representation and similarity measure suitable for content-based image retrieval"[J].Multimedia Systems,1999,7(2):165-174.
[146]Z.Hong,Q.Jiang."A kind of shape similarity measure methods and its performance evaluation"[J].Journal of Computational Information Systems,2007,3(5):2057-2062.
[147]张玲.商标图像检索研究与系统实现[D].湖南大学硕士学位论文,2006.
[148]蒋奉浩,路阳,章玉林.”最小二乘圆的新求法及其与国际通用算法的比较”[J].江苏计量测试,1999,1:42-45.
[149]P.Kumar,E.A.Yildirim."Minimum-volume enclosing ellipsoids and tory sets"[J].Journal of Optimization Theory and Applications,2005,126(1):1-21.
[150]计算几何算法库.http://www.cgal.org.
[151]B.Gartner,S.Schonherr."Exact primitives for smallest enclosing ellipses"[J].Information Processing Letters,1998,68(1):33-38.
[152]Y.Q.Xin,M,Pawlak,S.Liao."Accurate computation of Zernike moments in polar coordinates"[J].IEEE Transactions on Image Processing,2007,16(2):581-587.
[153]A.K.Jain,A.Vailaya."Shape-based retrieval:a case study with trademark image databases"[J].Pattern Recognition,2000,33(2):350-350.
[154]H.Jiang,C.W.Ngo,H.K.Tan."Gestalt-based feature similarity measure in trademark database"[J].Pattern Recognition,2006,39(5):985-1001.
[155]A.Cerri,M.Ferri,D.Giorgi."Retrieval of trademark images by means of size functions"[J].Graphical Models,2006,68(5-6):451-471.
[156]Z.Hong,Q.Jiang,M.Wu."Combining Block and Comer feature for Content-based Trademark Retrieval"[J].Wuhan University Journal of Natural Sciences,2007,12(5):907-911.
[157]Z.Hong,Q.Jiang."Hybrid Content-based Trademark Retrieval using Region and Contour Features"[C].Proceeding of the IEEE International Symposium on Mining the Asian Web,Okinawa,Japan,2008:1163-1168.
[158]找商标.http://www.looktm.com/.
[159]黄元元.基于视觉特征的图像检索技术研究[D].南京理工大学博士学位论文,2003.
[160]觅商网.http://www.tmsoso.com/.
[2]中华人民共和国国家工商行政管理总局.http://www.saic.gov.cn/.
[3]中华人民共和国国家知识产权局.http://www.sipo.gov.cn/sipo/.
[4]世界知识产权组织.http://www.wipo.int/portal/index.html.zh.
[5]中国知识产权在线.http://www.ipsoon.org/.
[6]中国商标专网(白兔商标查询).http://www.cha-tm.com/.
[7]德龙中国商标查询库.http://www.dltm.net/.
[8]北京商标网.http://www.pekingtm.cn/Articlc/2812.html.
[9]郭丽.基于内容的商标图像检索研究[D].南京理工大学博士学位论文,2003.
[10]中国商标数据库.http://www.86tm.com/.
[11]章毓晋.基于内容的视觉信息检索[M].北京:科学出版社,2003.
[12]J.P.Eakins,K.J.Riley,J.D.Edwards."Shape feature matching for trademark image retricval"[J].Image and Video Retrieval,Proceedings,2003,2728:28-38.
[13]Y.Huang,L.Guo."Binary trademark retrieval based on sub-block image"[J].Nanjing Hangkong Hangtian Daxue Xuebao/Journal of Nanjing University of Aeronautics and Astronautics,2006,38(6):737-742.
[14]B.J.Zou,Y.Yao,L.Zhang."A new algorithm for trademark image retrieval based on sub-block of polar coordinates"[C].Shanghai,China,Springer Verlag,Heidelberg;D-69121,Germany,2007,4740 NCS:91-97.
[15]章毓晋.图像工程(上册)-图像处理和分析[M].北京:科学出版社,1999.
[16]C.Shahabi,M.Safar."An experimental study of alternative shape-based image retrieval techniques"[J].Multimedia Tools and Applications,2007,32(1):29-48.
[17]N.Wei,M.E.Celebi,G.H.Geng."Content Based Retrieval and Classification of Cultural Relic Images"[C].Advances in Neural Networks-Isnn 2005:Second International Symposium on Neural Networks,Part 2,Proceedings,2005:292-298.
[18]章毓晋.图像理解与计算机视觉[M].北京:电子工业出版社,2000.
[19]R.C.Veltkamp,L.J.Latecki."Properties and Performance of Shape Similarity Measures"[C].10th IFCS Conf.Data Science and Classification,Slovenia,2006.
[20]M.Bober."MPEG-7 visual shape descriptors"[J].IEEE Transactions on Circuits and Systems for Video Technology,2001,11(6):716-719.
[21]L S.Hsieh,K.C.Fan."Multiple classifiers for color flag and trademark image retrieval"[J].IEEE Transactions on Image Processing,2001,10(6):938-950.
[22]B.Verma,M.Blumenstein,M.Ghosh."A novel approach for structural feature extraction:Contour vs.direction"[J].Pattern Recognition Letters,2004,25(9):975-988.
[23]P.Y.Yin,C.C.Yeh."Content-based retrieval from trademark databases"[J].Pattern Recognition Letters,2002,23(1-3):113-126.
[24]C.C.Waag,L.H.Chen."Content-based color trademark retrieval system using hit statistic"[J].International Journal of Pattern Recognition and Artificial Intelligence,2002,10(5):603-619.
[25]H.L.Peng,S.Y.Chen."Trademark shape recognition using closed contours"[J].Pattern Recognition Letters,1997,18(8):791-803.
[26]M.T.Chang,S.Y.Chen."Deformed trademark retrieval based on 2D pseudo-bidden Markov model"[J].Pattern Recognition,2001,34(5):953-967.
[27]M.S.Kankanhalli,B.M.Mehtre,H.Y.Huang."Color and spatial feature for content-based image retrieval"[J].Pattern Recognition Letters,1999,20(1):109-118.
[28]J.L.Shih,L.H.Chen."A new system for trademark segmentation and retrievar"[J].Image and Vision Computing,2001,19(13):1011-1018.
[29]G.Cortelazzo,et al."Trademark shapes description by string-matching techniques"[J].Pattern Recognition,1994,27(8):1005-1018.
[30]A.K Jain,A.Vailaya."Image Retrieval using Color and Shape"[J].Pattern Recognition,1996,29(8):1233-1244.
[31]C.H.Teh,R.H.Chin."On Image Analysis by the Method of Moments"[J].IEEE Trans.PAMI,1988,10(4):496-513.
[32]W.Y,Kim,Y.S.Kim."A region-based shape descriptor using Zernike moments"[J].Signal Processing-Image Communication,2000,16(1-2):95-102.
[33]S.D.Lin,et al."Trademark image retrieval by distance-angle pair-wise histogram"[J].International Journal of Imaging Systems and Technology,2005,15(2):103-113.
[34]姚玉荣,章毓晋.”利用小波和矩进行基于形状的图像检索”[J].中国图像图形学报,2000,5(3):206-210.
[35]J.P.Eakins,J.M.Boardman,M.E.Graham."Similarity retrieval of trademark image"[J].IEEE Multimedia,1998,5(2):53-63.
[36]M.Flickner."Query By Image and Video Content:The QBIC System"[J].IEEE Computers,1995.
[37]virage 公司.http://www.virage.com.
[38]Excalibur 技术公司.http://vrw.excalib.com.
[39]A.Pentland,R.W.Pioard,S.Solaroff."Photobook:Content-based Manipulation of Image Databases"[J].Internal Journal of Computer Vision,1996:34-47.
[40]T.P.Minks,R.W.Picard."Interactive learning with a society of models"[J].Pattern Recognition,1997,30(4):565-581.
[41]Visual SEEk.http://www.ctr.columbia.edu/VisualSEEK/.
[42]S.D.Servetto,et al."A region-based representation of images in MARS"[J].Journal of Vlsi Signal Processing Systems for Signal Image and Video Technology,1998,10(1-1):137-150.
[43]M.Ortega,et al."Supporting ranked Boolean similarity queries in MARS"[J].Ieee Transactions on Knowledge and Data Engineering,1998,10(6):905-925.
[44]M.Ortega-Binderberger,S.Mehrotra."Relevance feedback techniques in the MARS image retrieval system"[J].Multimedia Systems,2004,9(6):535-547.
[45]NETRA.http://maya.ece.ucsb.edu/Netra.
[46]C.Carson,et al."Blobworld:Image segmentation using expectation-maximization and its application to image querying"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,24(8):1026-1038.
[47]J.Li,J.Z.Wang."Automatic linguisfic indexing of pictures by a statistical modeling approach"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2003,25(9):1075-1088.
[48]I.J.Cox,et al."The Bayesian image retrieval system,PicHunter:Theory,implementation,and psychophysical experiments(vol 9,pg 20,2000)"[J].IEEE Transactions on Image Processing,2000,9(3):524-524.
[49]ImageRover.http://www.es.bu.edu/groups/ive/Imagerover.
[50]Surfimage.http://www.rocq.inria.fr/imedia.
[51]PICSearch.http://www.cs.helsinki.fi/～klemstro/picsearch.
[52]PicToSeek.http://zomax.wins.uva.nl:5345/zomax/html/zomax.html.
[53]M.Kokare,B.N.Chatterji,P.K.Biswas."A survey on current content based image retrieval methods"[J].Iete Journal of Research,2002,48(3-4):261-271.
[54]Han,Guo."A new image retrieval model supporting query by semantics and example"[C].IEEE Conference on Image Processing,2002.
[55]H.Jin,R.H.He,W.B.Tao."Exploring semantic association rules between keyword and visual feature clusters for web image retrieval"[J].Chinese Journal of Electronics,2008,17(1):59-65.
[56]X.Q.Zhu,et al."New query refinement and semantics integrated image retrieval system with semiautomatic annotation scheme"[J].Journal of Electronic Imaging,2001,10(4):850-860.
[57]S.Manjunath,et al."Color and Texture Descriptors"[J].IEEE Trans.on Circuit and Systems for Video Technology,2001.
[58]M.Ferecatu,N.Boujemaa,M.Crucianu."Semantic interactive image retrieval combining visual and conceptual content descripfion"[J].Multimedia Systems,2008,13(5-6):309-322.
[59]J.K.Wu."Content-baaed indexing of multimedia databases"[J],Ieee Transactions on Knowledge and Data Engineering,1997,9(6):978-989.
[60]X.M.Zhon,C.H.Ang,T.W.Ling."Indexing for multipoint interactive similarity retrieval in iconic spatial image databases"[J].Journal of Visual Languages and Computing,2008,19(1):24-38.
[61]S.Aouat,et al."3D object indexing and recognition"[J].Applied Mathematics and Computation,2008,196(1):318-332.
[62]Q.Zhang,E.Izquierdo."Combining low-level features for semantic extraction in image retrieval"[J].Eurasip Journal on Advances in Signal Processing,2007.
[63]T.Qin,et al."An active feedback framework for image retrieval"[J].Pattern Recognition Letters,2008,29(5):637-646.
[64]P.C.Cheng,et al."A two-level relevance feedback mechanism for image retrieval"[J].Expert Systems with Applications,2008,34(3):2193-2200.
[65]G.P.Nguyon,M.Worring."Optimization of interactive visual-similarity-baaed search"[J].Acm Transactions on Multimedia Computing Communications and Applications,2008,4(1):1-23.
[66]C.Liu,et al."Automatic estimation and removal of noise from a single image"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2008,30(2):299-314.
[67]M.R.Hejazi,Y.S.Ho."An efficient approach to texture-based image retrieval"[J].International Journal of Imaging Systems and Technology,2007,17(5):295-302.
[68]S.Kiranyaz,M.Ferreira,M.Gabbonj."A genetic shape/texture descriptor over multiscale edge field:2-D walking ant histogram"[J].IEEE Transactions on Image Processing,2008,17(3):377-391.
[69]郑南宁.计算机视觉与模式识别[M].北京:国防工业出版社,1998.
[70]张爱华.基于模糊聚类分析的图像分割技术研究[D].华中科技大学博士学位论文,2004.
[71]Q.Chen,et al."A double-threshold image binarization method based on edge detector"[J].Pattern Recognition,2008,41(4):1254-1267.
[72]W.Doyle."Operations Useful for Similarity-invariant Pattern Recognition"[J].Journal of ACM,1962,9(2):259-267.
[73]N.Otsu."A threshold selection method from gray-level histogram"[J].IEEE Trans on System Man Cybemet,1979:62-66.
[74]T.Pun."A New Method for Gray-level Picture Thresholding Using The Entropy of Histogram"[J].Signal Processing,1980,2:223-237.
[75]M.Sonka,V.Hlavac,R.Boyle.Image Processing,Analysis,and Machine Vision(Second Edition)[M].北京:人民邮电出版社,2003.
[76]K.Hammonche,M.Dial,P.Siarry."A multilevel automatic thresholding method based on a genetic algorithm for a fast image segmentation"[J].Computer Vision and Image Understanding,2008,109(2):163-175.
[77]A.D.Brink."Thresholding Digital Images Using Two-dimensional Entropics"[J].Pattern Recognition,1992,25(8):803-808.
[78]O.Laligant,F.Truchetet,F.Meriandeau."Regularization preserving localization of close edges"[J].IEEE Signal Processing Letters,2007,14(3):185-188.
[79]L.Matalas,R.Benjamin,R.Kitney."An Edge Detection Technique Using the Facet Modal and Parameterized Relaxation Labeling"[J].IEEE Trans on Pattern Analysis and Machine Intelligence,1997,19(4):328-341.
[80]J.Canny."A Cmputational Approach to Edge Dctection"[J].IEEE Trans Pattern Analysis and Machine Intelligence,1986,8(6):679-698.
[81]尹平,王润生.”自适应多尺度边缘检测”[J].软件学报,2000,11(B):990-994.
[82]X.B.Wen,H.Zhang,Z.Tian."A multiscale serf-growing probabilistic decision-based neural network for segmentation of SAR imagery"[C].Pricai 2006:Trends in Artificial Intelligence,Proceedings,2006,4099:1166-1170.
[83]R.Legault,C.Y.Suen."Optimal local weighted averaging methods in contour smoothing"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1997,19(8):801-817.
[84]H.D.Cheng,Y.Sun."A hierarchical approach to color image segmentation using homogeneity"[J].IEEE Transactions on Image Processing,2000,9(12):2071-2082.
[85]Y.T.Wu,et al."A top-down region dividing apprnaoh for image segmentation"[J].Pattern Recognition,2008,41(6):1948-1960.
[86]L.Vincent,S.Pierre."Watersheds in Digital Spaces:An Efficient Algorithm Breed on Immersion Simulations"[J].IEEE Transactions of Pattern Analysis and Machine Intelligence,1991,13(6):583-598.
[87]杨文明.时空联合的视频对象分割[D].浙江大学博士学位论文,2006.
[88]李相镐,李洪兴,陈世权.模糊聚类分析及其应用[M].贵阳:贵州科学技术出版社,1994.
[89]I.Bloch,G.Martino,A.Petrosino."A fuzzy mathematical morphology approach to multiseeded image segmentation"[J].Fuzzy Logic and Applications,2006,3849:362-368.
[90]Y.Fang,C.Pan,L.Liu."On-line training of neural network for color image segmentation"[C].Advances in Natural Computation,Pt 2,Proceedings,2005,3611:135-138.
[91]Q.Sun,et al."A fully unsupervised image segmentation algorithm breed on wavelet-domain hidden Markov tree models"[C].Advanced Concepts for Intelligent Vision Systems,Proceedings,2005,3708:507-514.
[92]K.E.Melkemi,M.Batouche,S.Foufou."A multiagent system approach for image segmentation using genetic algorithms and extremal optimization heuristics"[J].Pattern Recognition Letters,2006,27(11):1230-1238.
[93][美]K.R.Castlcman著、朱志刚等译.数字图像处理[M].清华大学出版社,1999.
[94]胡小锋,赵辉编著.Visual C++/matlab图像处理与识别实用案例精选[M].北京:人民邮电出版社,2004年9月.
[95]M.K.Hu."Visual Pattern Recognition by Moment Invariants"[J].IRE Trans.Info Theory,1962,IT-8:179-187.
[96]M.Teague."Image analysis via the general theory of moments"[J].Journal Optical America,1980,70(8):920-930.
[97]陈晓飞.基于骨架的目标表示和识别技术研究[D].国防科学技术大学博士学位论文,2004.
[98]S.Santini,R.Jain."Similarity measures"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1999,21(9):871-883.
[99]Y.Rubner,C.Tomasi,L.J.Guibas."A metric for distributions with applications to image database"[C].In 6th International Conference on Computer Vision,Bombay,India.,1998:59-66.
[100]S.Cohen,L.Guibas."The Mover's Distance under Transformation Sets"[C].The 7th IEEE International Conference on Computer Vision,Corfu,Greece,1999:173-187.
[101]M.Sharon,L.Ting-Sheng,T.John."Evaluating a content based image retrieval aystem"[C].In the proceedings of the 24th annual international ACM SIGIR conference on research and development in information retrieval,New Orleans,Louisiana,United States,2001:232-240.
[102]孙兴华,杨静宇.”基于子图像多特征组合的商标图像检索”[J].模式识别与人工智能,2002,15(1):14-20.
[103]赵晨光,宋利伟,庄天戈.”基于分水岭区域差异性的多级图像分割”[J].上海交通大学学报,2004,38(9):1489-1491.
[104]崔明,孙守迁,潘云鹤.“基于改进快速分水岭变换的图像区域融合”[J].计算机辅助设计与图形学学报,2005,17(3):546-552.
[105]H.P.Ng,et al."Masseter segmentation using an improved watershed algorithm with unsupervised classification"[J].Computers in Biology and Medicine,2008,38(2):171-184.
[106]J.Cousty,et el."Fusion graphs:Merging properties and watersheds"[J].Journal of Mathematical Imaging and Vision,2008,30(1):87-104.
[107]R.Lotufo,W.Silva."Minimal set of markers for the watershed transform"[C],International Symposium on Mathematical Morphology,ISMM2002,Australia,2002:359-368.
[108]J.Park,J.M.Keller."Snakes on the watershed"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2001,23(10):1201-1205.
[109]龚剑.”一种基于分水岭和模糊聚类的多级图像分割算法”[J].第—军医大学学报,2004,24(3):32-33.
[110]Z.Hong,et el."Measuring Overlap-rate in Hierarchical Cluster Merging for Image Segmentation and Ship Detection"[C].Proceeding of the 4th International Conference on Fuzzy Systems and Knowledge Discovery,2007,4:420-424.
[111]洪志令,et al.“基于分水岭和重叠率衡量的多级彩色图像分割”[J].中国图象图形学学报,2008年出版.
[112]洪志令,姜青山,王声瑞.”基于重叠率衡量融合策略的层次聚类算法研究”[J].计算机研 究与发展,2007,44(Suppl.):117-122.
[113]Z.Hong,Q.Jiang,S.Wang."Measuring Overlap-Rate in a Hierarchical Approach for Color Image segmentation"[C].Proceeding of the 2nd International Conference on Innovative Computing,Information and Control,ICICIC,2007:442-446.
[114]International Color Consortium.www.color.org.
[115]S.Arora,et al."Multilevel thresholding for image segmentation through a fast statistical recursive algorithm"[J].Pattern Recognition Letters,2008,29(2):119-125.
[116]S.Wang,H.Sun."Measuring Overlap-Rate for Cluster Merging in a Hierarchical Approach to Color Image Segmentation"[J].International Journal of Fuzzy Systems,2004,6(3).
[117]D.Martin,et al."A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics"[C].ICCV,2001,2:416-423.
[118]D.R.Martin,C.C.Fowlkes,J.Malik."Learning to detect natural image boundaries using local brightuess,color,and texture cued'[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2004,26(5):530-549.
[119]卢汉清,et al.”基于内容的视频信号与图像库检索中的图像技术”[J].自动化学报,2001,27(1):56-69.
[120]黄元元,郭丽,杨靖宇.”基于形状与空间特征的二值商标图像检索”[J].模式识别与人工智能,2003 16(2):241-245.
[121]B.Luo,R.C.Wilson,E.R.Hancock."Spectral embedding of graphs"[J].Pattern Recognition,2003,36(10):2213-2230.
[122]T B.Sebastian,P.N.Klein,B.B.Kimia."Recognition of shapes by editing their shock graphs"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2004,26(5):550-571.
[123]H.F.Zhao,M.Kong,B.Luo."Shape representation based on polar-graph spectra"[J].Intelligent Computing in Signal Processing and Pattern Recognition,2006,345:900-905.
[124]N.M.Tahir,et al "Shook graph for repres entation and modeling of posture"[J].Etri Journal,2007,29(4):507-515.
[125]赵海峰.基于图的形状描述方法研究[D].安徽大学博士学位论文,2006.
[126]Z.Hong,Q.Jiang."Shape Image Retrieval based on Comer Delaunay Triangulation"[J].Journal of Computational Information Systems,2007,3(5):1861-1866.
[127]Z.Hong,Q.Jiang,X.Wei."Shape Representation and Similarity Measure Based on Delaunay Triangulation"[J].Journal of Cruangxi Normal University,2007,25(4):261-264.
[128]S.M.Smith,J.M.Brady."SUSAN-A new approach to low level image prooessing"[J].International Journal of Computer Vision,1997,23(1):45-78.
[129]H.X.C,Y.N.H.C."Curvature scale space corner detector with adaptive threshold and dynamic region of support"[C].Proc 17th International Conference on Pattern Recognition.Cambridge,UK,2004:791-794.
[130]H.Haron,S.M.Shamsuddia,D.Mohamed."A new corner detection algorithm for chain code representation"[J].International Journal of Computer Mathematics,2005,82(8):941-950.
[131]Freeman.H,Davis.L.S."A comer finding algorithm for chaincoded curves"[J].IEEE Transactions on Computers,1977,C26(3):297-303.
[132]H.Wang,C.S.Chug C.T.Sim."Real-time object tracking from corners"[J].Robotica,1998,16:109-116.
[133]C.Harris,M.Stephens."A combined corner and edge detector"[C].In Alvey Virion Conference,Cambridge,UK,1987:147-151.
[134]孟坛魁,华成英.”一种改进的灰度图像角点检测算法”[J].计算机应用研究,2005,4:105-106,129.
[135]F.Mokhtarian,R.Suomela."Robust image corner detection through curvature scale space"[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1998,20(12):1376-1381.
[136]F.Mokhtarian,F.Mohanna."Enhancing the curvature scale space corner detector"[C].Prec.Scandinavian Conference on Image Analysis,Bergen,Norway,,2001:145-152.
[137]刘广海.基于纹理和形状特征的图像检索技术研究[D].南京理工大学硕士学位论文,2004.
[138]Y.Tao,W.I.Grosky."Delaunay triangulation for image object indexing:A novel method for shape representation"[C].In Proceedings of the Seventh SPIE Symposium on Storage and Retrieval for Image and Video Databases,1999:631-942.
[139]R.A.Dwyer."A Faster Divide-and-Conquer Algorithm for Constructing Delauaay Triangulations"[J].Algorithmic,1987,2(2):127-151.
[140]Zhou.D.X,Li.G.H,Liu.Y.H."Effective corner matching based on delaunay triangulation"[C].IEEE International Conference on Robotics and Automation,New Orleans,LA,USA,2004:2730-2735.
[141]E.R.van Dam,W.H.Haemers."Which graphs are determined by their spectrum?"[J].Linear Algebra and Its Applications,2003,373:241-272.
[142]范益政.图的谱理论[D].中国科学技术大学博士学位论文,2001.
[143]B.Xiao,H.Yu,E.Hancock."Graph matching using manifold embedding"[C].Image Analysis and Recognition,Pt 1,Proceedings,2004,3211:352-359.
[144]J.Han,M.Kamber.Data Mining:Conceptes and Techniques[M].China Machine Press,2006.
[145]G.J.Lu,A.Sajjanhar."Region-based shape representation and similarity measure suitable for content-based image retrieval"[J].Multimedia Systems,1999,7(2):165-174.
[146]Z.Hong,Q.Jiang."A kind of shape similarity measure methods and its performance evaluation"[J].Journal of Computational Information Systems,2007,3(5):2057-2062.
[147]张玲.商标图像检索研究与系统实现[D].湖南大学硕士学位论文,2006.
[148]蒋奉浩,路阳,章玉林.”最小二乘圆的新求法及其与国际通用算法的比较”[J].江苏计量测试,1999,1:42-45.
[149]P.Kumar,E.A.Yildirim."Minimum-volume enclosing ellipsoids and tory sets"[J].Journal of Optimization Theory and Applications,2005,126(1):1-21.
[150]计算几何算法库.http://www.cgal.org.
[151]B.Gartner,S.Schonherr."Exact primitives for smallest enclosing ellipses"[J].Information Processing Letters,1998,68(1):33-38.
[152]Y.Q.Xin,M,Pawlak,S.Liao."Accurate computation of Zernike moments in polar coordinates"[J].IEEE Transactions on Image Processing,2007,16(2):581-587.
[153]A.K.Jain,A.Vailaya."Shape-based retrieval:a case study with trademark image databases"[J].Pattern Recognition,2000,33(2):350-350.
[154]H.Jiang,C.W.Ngo,H.K.Tan."Gestalt-based feature similarity measure in trademark database"[J].Pattern Recognition,2006,39(5):985-1001.
[155]A.Cerri,M.Ferri,D.Giorgi."Retrieval of trademark images by means of size functions"[J].Graphical Models,2006,68(5-6):451-471.
[156]Z.Hong,Q.Jiang,M.Wu."Combining Block and Comer feature for Content-based Trademark Retrieval"[J].Wuhan University Journal of Natural Sciences,2007,12(5):907-911.
[157]Z.Hong,Q.Jiang."Hybrid Content-based Trademark Retrieval using Region and Contour Features"[C].Proceeding of the IEEE International Symposium on Mining the Asian Web,Okinawa,Japan,2008:1163-1168.
[158]找商标.http://www.looktm.com/.
[159]黄元元.基于视觉特征的图像检索技术研究[D].南京理工大学博士学位论文,2003.
[160]觅商网.http://www.tmsoso.com/.