International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 1, No. 1, 8 Oct. 2009
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Hierarchical Matching for Chinese Calligraphic Retrieval Using Skeleton Similarity
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Index Terms
Hierarchical matching, calligraphic retrieval, skeleton similarity
Abstract
Individual Chinese characters are identified mainly by their skeleton structure instead of texture or color.In this paper, an approach based on skeleton similarity for Chinese calligraphic characters retrieval is proposed.By this approach,first,the skeleton of the binarized individual characters are acquired by an improved multi-level module analysis algorithm.Second,the first round of skeleton matching based on the invariant moment-descriptor guarantees the recall rate;the second round of skeleton matching based on the comprehensive characteristic difference in the polar coordinates system guarantees the retrieval precision.Finally,different styles of the same Chinese characters are ranked and displayed according to the two rounds of matching score.Besides,the efficiency of our approach is manifested by the preliminary experiment.
Cite This Paper
Jie Chen, Fuxi Zhu, "Hierarchical Matching for Chinese Calligraphic Retrieval Using Skeleton Similarity", International Journal of Information Technology and Computer Science(IJITCS), vol.1, no.1, pp.41-48, 2009. DOI: 10.5815/ijitcs.2009.01.06
Reference
[1] Palmondon R, Srihari S N. On-line and off-line handwriting recognition:A comprehensive survey[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2000,22(1):63-84.
[2] Rath T M, Kane S,Lehman A.Indexing for a digital library of George Washington’s manuscripts:A study of word matching techniques[R]. Massachusetts: Center for Intelligent Information Retrieval, Computer Science Department, University of Massachusetts,2004
[3] Itay Bar Yosef, Klara Kedem, et al. Classification of Hebrew calligraphic handwriting style[A]. In: Proceedings of the 1st International Workshop on Document Image Analysis for Libraries, Palo Alto, California,2006.299-305
[4] Shi Baile, Zhang Liang, Wang Yong , et al. Content-based Chinese script retrieval through visual similarity criteria[J]. Journal of Software,2001,12(9):1336-1342(in Chinese)
[5] Zhang Xiafen, Zhuang Yueting , et al.Chinese calligraphic chracter retrieval based on shape similarity[J]. Journal of Computer-Aid Design & Computer Graphics,2005,17(11):2565-2569)
[6] Wu Youshou, Ding Xiaoqing. Chinese Chracter Recognition: Theory, Approach and Implementation[M].Beijing: High Education Press,1992(in Chinese)
[7] Zhang KuangZhong . Chinese Character Recognition Technology[M].Beijing: Tsinghua University Press,1992(in Chinese)
[8] John Canny. A computational approach to edge detection[J]. In: IEEE transactions Pattern Analysis and Machine Intelligence,1986,11(2),678-698.
[9] Blum H. A transformation for extracting new description of shape[A]. In Wathen-Dunn W ed. Model for the Perception of Speech and Visual[C].Cambiride, Massachusetts: MIT Press,1967.362-380
[10] Zhao chunjinag, Shi wenkang. A robust algorithm for distilling the skeletons of images[J]. Computaer Appliacation,2005,6(1),1305-1306(in Chinese)
[11] Wan Hualin, Morshed U, Hu Hong, etal. Texture feature and its application in CBIR[J]. Journal of Computer-Aid Design & Computer Graphics, 2003,15(2):195-199(in Chinese) products of Bessel functions,” Phil. Trans. Roy. Soc. London, vol. A247, pp. 529–551, April 1955.
[12] Haili Chui, Anad, Rangrarajan. A new point matching algorithm for non-rigid registration[J]. Computer Vision and Image Understanding archive,2003,89(2):114-14
[13] L u Y, Zhang H J , Yin L W , et al. Joint semantic and feature based image retrieval using relevance feedback [J ]. IEEE Transaction on Multimedia, 2003, 5 (3) : 3392347.
[14] Inoue T, A be S. Fuzzy support vector machines for pattern classification[C ]. In: Proceedings of International Joint Conference on N eural Networks ( IJCNN ’01) , July 2001, 2: 1449-1454.
[15] A be S, Inoue T. Fuzzy support vector machines for multiclass problems [C ]. In: Proceedings of the Tenth European Symposium on Artificial Neural Networks (ESANN " 2002) , Bruges,Belgium, April 2002, 113-118.
[16] Wang Shang fei, Xue J ia, W ang Xifa. Contented-based emotion image retrievalmodel[J]. Computer Science, 2004, 31 (9) : 186-190.
[17] Hsia T C. A note on invariantmoments in image processing[J ].IEEE Trans. On SMC, 1981, 11 (12) : 831-834.
[18] Vapnik V N. Statistical learning theory [M ]. John W iley &Sons, NewYork, N Y, 1998.
[19] Abe S. Analysis of multiclass support vector machines[C ]. In:Proceedings of International Conference on Computational Intelligence fo rModelling Control and Automation (C IMCA ’2003) ,Vienna, Austria, February 2003, 385-396.
[20] Xu Yang.Chinese Calligraphy Production Method Based on HMM Genetics Analogy[J].Journal of Wuhan University,2008,54(1):85-89.
[21] Xu Song Hua,Lau Francis,Cheung William K,Pan Yun.He.Auto matic generation of artistic Chinese calligraphy.IEEE Intelligent Systems,2005,20(3):32-39
[22] Zhang Jun-song,Yu Jin-hui,Mao Guo-hong,Ye Xiu-zhi.Generating Brush Texture for Cursive Style Calligraphy with Auto regressive and Stratified Sampling[J].Journal of Computer-Aided Design & Computer Graphics, 2007, 19(11): 1399-1403.
[23] Dong Jun,Xu Miao,Pan Yun-he,Ye. Statistic Model-Based Simulation on Calligraphy Creation [J].Chinese Journal of Computers, 2008, 31(7): 7720-7725