Computer Science ›› 2019, Vol. 46 ›› Issue (7): 30-37.doi: 10.11896/j.issn.1002-137X.2019.07.005
• Surveys • Previous Articles Next Articles
WU Gang,XU Li-min
CLC Number:
[1]KURNIANGGORO L,WAHYON O,JO K H.A survey of 2d shape representation:Methods,evaluations,and future research directions[J].Neurocomputing,2018,300:1-16. [2]ZHANG D S,LU G J.Review of shape representation and description techniques[J].Pattern Recognition,2004,37(1):1-19. [3]KAZMI I K,YOU L,ZHANG J J.A survey of 2d and 3d shape descriptors[C]∥2013 10th International Conference Computer Graphics,Imaging and Visualization.Macau:IEEE Press,2013:1-10. [4]DUAN L J.A Survey of Shape Feature[J].Computer Secience,2007,34(8):215-218.(in Chinese) 段立娟.形状特征的编码描述研究综述[J].计算机科学,2007,34(8):215-218. [5]DEMISSE G G,AOUADA D,OTTERSTEN B.Deformation based curved shape representation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2018,40(6):1338-1351. [6]MASON J C,HANDSCOMB D.Chebyshev Polynomials[M].Berlin:Chapman & Hall/CRC,2003:20-30. [7]HEIZER A,BARZOHAR M,MALAH D.Stable fitting of 2d curves and 3d surfaces by implicit polynomials[J].IEEE Tran-sactions Pattern Analysis and Machine Intelligence,2004,26(10):1283-1294. [8]WU G,ZHANG Y C.A novel fractional implicit polynomial approach for stable representation of complex shapes[J].Journal of Mathematical Imaging and Vision,2016,55(1):89-104. [9]OLIVEIRA A B D,SILVA P,DA C R,et al.A novel 2d shape signature method based on complex network spectrum[J].Pattern Recognition Letters,2015,63:43-49. [10]NIXON M,AGUADO A S.Feature Extraction and Image Pro- cessing for Computer Vision[M].London:Academic Press,2012:100-121. [11]ZHANG G,MA Z M,NIU L Q,et al.Modified fourier descriptor for shape feature extraction[J].Journal of Central South University,2012,19(2):488-495. [12]WU G Y,ZHANG Y C.A new chebyshev polynomials descriptor applicable to open curves[J].Pattern Recognition Letters,2015,62:41-48. [13]WU H Y,YAN S L.Computing invariants of tchebichef moments for shape based image retrieval[J].Neurocomputing,2016,215(26):110-117. [14]Mukundan R,Ong S H,Lee P A.Image analysis by tchebichef moments[J].IEEE Transactions on Image Processing,2001,10(9):1357-1364. [15]PEE C Y,ONG S H,RAVEENDRAN P.Numerically efficient algorithms for anisotropic scale and translation tchebichef moment invariants[J].Pattern Recognition Letters,2017,92:68-74. [16]CHEN Z,SUN S K.A zernike moment phase-based descriptor for local image representation and matching[J].IEEE Transactions on Image Processing,2010,19(1):205-219. [17]HU M K.Visual Pattern Recognition by Moment Invariants [J].IRE Transactions on Information Theory,1962,8(2):179-187. [18]SAJJANHAR A.A technique for similarity retrieval of shapes[D].Melbourne:Monash University,1997:80-90. [19]ROUHANI M,SAPPA A D.Implicit polynomial representation through a fast fitting error estimation[J].IEEE Transactions on Image Processing,2012,21(4):2089-2098. [20]TEAGUE M R.Image analysis via the general theory of mo- ments[J].Journal of the Optical Socient of America,1980,70(8):920-930. [21]WANG K J,ZHANG H G,CHAI L S,et al.A comparative study of moment-based shape descriptors for product image retrieval[C]∥2011 International Conference on Image Analysis and Signal Processing.Hubei:IEEE press,2011:355-359. [22]ROUHANI M,SAPPA A D,Boyer E.Implicit b-spline surface reconstruction[J].IEEE Transactions on Image Processing,2015,24(1):22-32. [23]EL-GHAZAL A,BASIR O,BELKASIM S.Farthest point dis- tance:A new shape signature for fourier descriptors[J].Signal Processing:Image Communication,2009,24(7):572-586. [24]BAI X,RAO C,WANG X.Shape vocabulary:A robust and efficient shape representation for shape matching[J].IEEE Tran-sactions on Image Processing,2014,23(9):3935-3949. [25]DALIRI M R,TORRE V.Robust symbolic representation for shape recognition and retrieval[J].Pattern Recognition,2008,41(5):1782-1798. [26]LIN C,PUN C M,VONG C M,et al.Efficient shape classification using region descriptors[J].Multimedia Tools and Applications,2017,76(1):83-102. [27]MOUINE S,YAHIAOUI I,VERROUST-BLONDET A.A shape-based approach for leaf classification using multiscale triangular representation[C]∥Proceedings of the 3rd ACM Conference on Multimedia Retrieval.Dallas:ACM press,2013:127-134. [28]ALAJLAN N,RUBE I E,KAMEL M S,et al.Shape retrieval using triangle-area representation and dynamic space warping[J].Pattern Recognition,2007,40(7):1911-1920. [29]HU R,JIA W,LING H,et al.Multiscale distance matrix for fast plant leaf recognition[J].IEEE Transactions on ImageProces-sing,2012,21(11):4667-4672. [30]HU R,JIA W,LING H,et al.Angular pattern and binary angular pattern for shape retrieval[J].IEEE Transactions on Image Processing,2014,23(3):1118-1127. [31]WANG B,GAO Y.Hierarchical string cuts:A translation,rotation,scale,and mirror invariant descriptor for fast shape retrie-val[J].IEEE Transactions on Image Processing,2014,23(9):4101-4111. [32]LI M,YUAN B Z.2d-lda:A statistical linear discriminant analysis for image matrix[J].Pattern Recognition Letters,2005,26(5):527-532. [33]BELONGIE S,MALIK J,PUZICHA J.Shape matching and object recognition using shape contexts[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,24(4):509-522. [34]ZHAO L,PENG Q Q,HUANG B Q.Shape matching algorithm based on shape contexts[J].IET Computer Vision,2015,9(5):681-690. [35]AN G,YU W.Captcha recognition algorithm based on the relative shape context and point pattern matching[C]∥2017 9th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA).Changsha:IEEE press,2017:168-172. [36]BOUAGAR S,LARABI S.Discriminative outlines parts for shape retrieval[J].Journal of Visual Communication and Image Representation,2015,33:149-164. [37]ZHU Z T,WANG X G,BAI S,et al.Deep learning representation using autoencoder for 3d shape retrieval[J].Neurocompu-ting,2016,204:41-50. [38]ASADA H,BRADY M.The curvature primal sketch[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1986,8(1):2-14. [39]BERRADA F,ABOUTAJDINE D,OUATIK S E,et al.Review of 2d shape descriptors based on the curvature scale space approach[C]∥2011 International Conference on Multimedia Computing and Systems.Ouarzazate:IEEE press,2011:1-6. [40]ADAMEK T,O’CONNOR N E.A multiscale representation method for nonrigid shapes with a single closed contour[J].IEEE Transactions on Circuits and Systems for Video Techno-logy,2004,14(5):742-753. [41]HONG B,SOATTO S.Shape matching using multiscale integral invariants[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2015,37(1):151-160. [42]HONG B W,PRADOS E,SOATTO S,et al.Shape representation based on integral kernels:Application to image matching and segmentation[C]∥2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.New York:IEEE press,2006:833-840. [43]ANDREA C G.Metrics of Curves in Shape Optimization and Analysis[M].Cham:Springer International Publishing,2013:205-319. [44]Younes L.Computable elastic distances between shapes[J].SIAM Journal on Applied Mathematics,1998,58(2):565-586. [45]YOUNES L.Parametrized Plane Curves[M].Berlin:Springer Berlin Heidelberg,2010:1-42. [46]YOUNES L.Optimal matching between shapes via elastic de- formations[J].Image and Vision Computing,1999,17(5):381-389. [47]GEMMEKE J F,ELLIS D P W,FREEDMAN D,et al.Audio set:An ontology and human-labeled dataset for audio events[C]∥2017 IEEE International Conference on Acoustics,Speech and Signal Processing.LA:IEEE press,2017:776-780. [48]ZEILER M D,FERGUS R.Visualizing and understanding con- volutional networks[M]//Computer Vision ECCV 2014.Berlin:Springer,2014:818-833. [49]LECUN Y,BENGIO Y S.Deep learning[J].Nature,2015,521(7553):436-444. [50]NASCIMENTO J C,CARNEIRO G.Deep learning on sparse manifolds for faster object segmentation[J].IEEE Transactions on Image Processing,2017,26(10):4978-4990. |
[1] | YAN Rui, LIANG Zhi-yong, LI Jin-tao, REN Fei. Predicting Tumor-related Indicators Based on Deep Learning and H&E Stained Pathological Images:A Survey [J]. Computer Science, 2022, 49(2): 69-82. |
[2] | YUAN Xiao-lei, YUE Xiao-feng, FANG Bo, MA Guo-yuan. Three-dimensional Target Recognition Method Based on Pair Point Feature and HierarchicalComplete-linkage Clustering [J]. Computer Science, 2021, 48(6A): 127-131. |
[3] | SUN Wen-yun, JIN Zhong, ZHAO Hai-tao, CHEN Chang-sheng. Cross-domain Few-shot Face Spoofing Detection Method Based on Deep Feature Augmentation [J]. Computer Science, 2021, 48(2): 330-336. |
[4] | JIAO Dong-lai, WANG Hao-xiang, LYU Hai-yang, XU Ke. Road Surface Object Detection from Mobile Phone Based Sensor Trajectories [J]. Computer Science, 2021, 48(11A): 283-289. |
[5] | LI Yuan-tong, LUO Yu-sheng, ZHU Zhen-min. Tongue Image Analysis in Traditional Chinese Medicine Based on Deep Learning [J]. Computer Science, 2020, 47(11): 148-158. |
[6] | PANG Yu, LIU Ping, LEI Yin-jie. Realization of “Uncontrolled” Object Recognition Algorithm Based on Mobile Terminal [J]. Computer Science, 2019, 46(6A): 153-157. |
[7] | HAO Wen, WANG Ying-hui, NING Xiao-juan, LIANG Wei and SHI Zheng-hao. Survey of 3D Object Recognition for Point Clouds [J]. Computer Science, 2017, 44(9): 11-16. |
[8] | WANG Jian, BAI He-xiang and LI De-yu. High Resolution Remote Sensing Image Object Recognition Algorithm Based on SIFT and Non-parametric Bayes [J]. Computer Science, 2017, 44(1): 289-294. |
[9] | LIU Tao, WU Ze-min, JIANG Qing-zhu, ZENG Ming-yong and PENG Tao-pin. Fast Object Recognition Method Based on Objectness [J]. Computer Science, 2016, 43(7): 73-76. |
[10] | WANG Yan-qing,CHEN De-yun,SHI Chao-xia,LIU Bo,FANG Guo-zhi. Object Recognition Based on a New Method of Edge Crawling [J]. Computer Science, 2010, 37(8): 266-269272. |
[11] | LEI Bao-quan, YANG Li-hua, CHENG Yong-mei, ZHAO Chun-hui, WU Yan-ru. Natural Object Recognition Algorithm Based on SVM and Coloexture Combination Features [J]. Computer Science, 2009, 36(10): 274-276. |
[12] | . [J]. Computer Science, 2006, 33(8): 229-231. |
[13] | WEI Li, WU Zhong-fu, LI Yun ,GU Yi (College of Computer, Chongqing University, Chongqing 400044). [J]. Computer Science, 2006, 33(5): 238-240. |
[14] | . [J]. Computer Science, 2006, 33(11): 228-232. |
|