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An Improved Color Cooccurrence Matrix Texture Descriptor |
XU Shao-Ping1,LI Chun-Quan1,2,HU Ling-Yan1,YANG Xiao-Hui1,2,JIANG Shun-Liang1 |
1.School of Information Engineering,Nanchang University,Nanchang 330031 2.School of Mechanical Electrical Engineering,Nanchang University,Nanchang 330031 |
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Abstract Utilizing similarity measure defined by the fuzzy continuous t-norm operator to describe the degree of difference between pixels in color images,an improved color cooccurrence matrix texture descriptor is proposed. In accordance with the predefined interval of distances and directions,the multi-channel color information of original color image is effectively integrated and converted to pseudo-gray images. Then,gray level cooccurrence matrix (GLCM) texture method is used to extract feature vector for the pseudo-gray image. A large number of experiments are performed on the content-based image retrieval prototype platform and the results show that compared with other types of texture descriptors,the improved texture descriptor has the same feature vector dimension as the GLCM descriptor,while its description ability matches with all kinds of color cooccurrence matrix descriptor. The improved texture descriptor effectively achieves the integration of texture and color characteristics and improves the image retrieval performance.
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Received: 21 February 2012
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[1] Penatti O,Valle E,Torres R. Comparative Study of Global Color and Texture Descriptors for Web Image Retrieval. Journal of Visual Communication and Image Representation,2012,23(2): 359-380 [2] Wang Xiangyang,Yu Yongjian,Yang Hongying. An Effective Image Retrieval Scheme Using Color,Texture and Shape Features. Computer Standards Interfaces,2011,33(1): 59-68 [3] Konstantinidis K,Gasteratos A,Andreadis I. Image Retrieval Based on Fuzzy Color Histogram Processing. Optics Communications,2005,248(4/5/6): 375-386 [4] Xu Shaoping,Zhang Hua,Jiang Shunliang,et al. Image Similarity Measure Based on Intuitionistic Fuzzy Set. Pattern Recognition and Artificial Intelligence,2009,22(1): 156-161 (in Chinese) (徐少平,张 华,江顺亮,等.基于直觉模糊集的图像相似性度量.模式识别与人工智能,2009,22(1): 156-161) [5] Sun Junding,Wu Xiaosheng. Content-Based Image Retrieval Based on Texture Spectrum Descriptors. Journal of Computer-Aided Design Computer Graphics,2010,22(3): 516-520 (in Chinese) (孙君顶,毋小省.纹理谱描述符及其在图像检索中的应用.计算机辅助设计与图形学学报,2010,22(3): 516-520) [6] Haralick R,Shangmugam K,Dinstein I. Textural Feature for Image Classification. IEEE Trans on Systems,Man and Cybernetics,1973,3(6): 610-621 [7] Lin Chuenhorng,Chen Rongtai,Chan Yungkuan. A Smart Content-Based Image Retrieval System Based on Color and Texture Feature. Image and Vision Computing,2009,27(6): 658-665 [8] Liu Guanghai,Zhang Lei,Hou Yingkun,et al. Image Retrieval Based on Multi-Texton Histogram. Pattern Recognition,2010,43(7): 2380-2389 [9] Liu Guanghai,Li Zuoyong,Zhanglei,et al. Image Retrieval Based on Micro-Structure Descriptor. Pattern Recognition,2011,44(9): 2123-2133 [10] Huang Di,Shan Caifeng,Ardabilian M,et al. Local Binary Patterns and Its Application to Facial Image Analysis. IEEE Trans on Systems,Man and Cybernetics,2011,41(6): 765-781 [11] Han Ju,Ma Kaikuang. Rotation-Invariant and Scale-Invariant Gabor Features for Texture Image Retrieval. Image and Vision Computing,2007,25(9): 1474-1481 [12] Ilea D,Whelan P. Image Segmentation Based on the Integration of Color-Texture Descriptors-A Review. Pattern Recognition,2011,44(10/11): 2479-2501 [13] Yue Jun,Li Zhenbo,Liu Lu,et al. Content-Based Image Retrieval Using Color and Texture Fused Features. Mathematical and Computer Modeling,2011,54(3): 1121-1127 [14] Huang J,Kumar S,Mitra M,et al. Image Indexing Using Color Correlograms // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. Puerto Rico,USA,1997,762-768 [15] Palm C. Color Texture Classification by Integrative Co-Occurrence Matrices. Pattern Recognition,2004,37(5): 965-976 [16] Maheswari G,Ramar K,Manimegalai D,et al. An Adaptive Region Based Color Texture Segmentation Using Fuzzified Distance Metric. Applied Soft Computing,2011,11(2): 2916-2914 [17] Zadeh L A. Fuzzy Sets. Information and Control,1965,8(3): 338-353 [18] Chaira T,Ray A. Fuzzy Measures for Color Image Retrieval. Fuzzy Sets and Systems,2005,150(3): 545-560 [19] George A,Veeramani P. On Some Results in Fuzzy Metric Spaces. Fuzzy Sets and Systems,1994,64(3): 395-399 [20] Kim J K,Park H W. Statistical Textural Features for Detection of Microcalcifications in Digitized Mammograms. IEEE Trans on Medical Imaging,1999,18(3): 231-238 [21] Camarena J G,Gregori V,Morillas S,et al. Fast Detection and Removal of Impulsive Noise Using Peer Groups and Fuzzy Metrics. Journal of Visual Communication and Image Representation,2008,19(1): 20-29 |
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