1. 南昌大学 信息工程学院 南昌 330031
2. 南昌大学 机电工程学院 南昌 330031
3. Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada K1S 5B6
Texture Descriptor Based on Spatial Statistical Features of Local Binary Pattern Code Pair
XU Shao-Ping1, LIU Xiao-Ping1, 3, LI Chun-Quan1, 2, HU Ling-Yan1, YANG Xiao-Hui1, 2
1. School of Information Engineering, Nanchang University, Nanchang 330031
2. School of Mechanical Electrical Engineering, Nanchang University, Nanchang 330031
3. Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada K1S 5B6
The local binary pattern(LBP) descriptors employed in the content-based image retrieval system lack the abilities to describe the spatial relationships and have longer dimension of feature vector. In this paper, an improved LBP (ILBP) texture descriptor based on spatial statistical feature of LBP code pair is proposed. The original image is converted to the LBP pseudo image using LBP coding method for micro-pattern, and then several statistics of LBP code pair are extracted to form the feature vector for describing the texture attributes of images. Experiments are preformed on the content-based image retrieval prototype platform. Experimental results show that compared with other LBP descriptors the ILBP descriptor further enhances the description ability of LBP descriptor and substantially reduces the feature vector dimension with better query accuracy and query efficiency.
徐少平, 刘小平, 李春泉, 胡凌燕, 杨晓辉. 基于LBP值对空间统计特征的纹理描述符[J]. 模式识别与人工智能, 2013, 26(8): 769-776.
Xu-Shao-Ping, LIU Xiao-Ping, LI Chun-Quan, HU Ling-Yan, YANG Xiao-Hui. Texture Descriptor Based on Spatial Statistical Features of Local Binary Pattern Code Pair. , 2013, 26(8): 769-776.
[1] Penatti O A B, Valle E, Torres R S. 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] Xu Shaoping, Li Chunquan, Hu Lingyan, et al. An Improved Color Cooccurrence Matrix Texture Descriptor. Pattern Recognition and Artificial Intelligence, 2013, 26(1): 90-98 (in Chinese)
(徐少平,李春泉,胡凌燕,等.一种改进的颜色共生矩阵纹理描述符.模式识别与人工智能, 2013, 26(1): 90-98)
[3] 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)
[4] Konstantinidis K, Gasteratos A, Andreadis I. Image Retrieval Based on Fuzzy Color Histogram Processing. Optics Communications, 2005, 248(4/5/6): 375-386
[5] Haralick R M, Shangmugam K, Dinstein I. Textural Feature for Image Classification. IEEE Trans on Systems, Man and Cybernetics, 1973, 3(6): 610-621
[6] Lin C H, 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
[7] Liu Guanghai, Zhang Lei, Hou Yingkun, et al. Image Retrieval Based on Multi-Texton Histogram.Pattern Recognition, 2010, 43(7): 2380-2389
[8] Liu Guanghai, Zhang Lei, Hou Yingkun, et al. Image Retrieval Based on Micro-Structure Descriptor. Pattern Recognition, 2011, 44(9): 2123-2133
[9] Zhang Lihe, Zhu Lili, Mi Xiaoli. Localized Multi-Channel Level Set Segmentation Combined with Gabor Texture Feature. Acta Electronica Sinica, 2011, 39(7): 1569-1574 (in Chinese)
(张立和,朱莉莉,米晓莉.结合Gabor纹理特征的局域化多通道水平集分割方法.电子学报, 2011, 39(7): 1569-1574)
[10] Ojala T, Pietikinen M, Menp T. Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Pa-tterns. IEEE Trans on Pattern Analysis and Machine Intelligence, 2002, 24(7): 971-987
[11] Nanni L, Lumini A, Brahnam S. Survey on LBP Based Texture Descriptors for Image Classification. Expert Systems with Applications, 2012, 39(3): 3634-3641
[12] Huang Di, Shan Caifeng, Ardabilian M, et al. Local Binary Pa-tterns and Its Application to Facial Image Analysis: A Survey. IEEE Trans on Systems, Man and Cybernetics, 2011, 41(6): 765-781
[13] Nanni L, Lumini A. A Reliable Method for Cell Phenotype Image Classification. Artificial Intelligence in Medicine, 2008, 43(2): 87-97
[14] Zhang Lun, Chu Rufeng, Xiang Shiming, et al. Face Detection Based on Multi-Block LBP Representation // Proc of the International Conference on Advances in Biometrics. Seoul, South Korea, 2007: 11-18
[15] Liao S, Law M W K, Chung A C S. Dominant Local Binary Pa-tterns for Texture Classification. IEEE Trans on Image Processing, 2009, 18(5): 1107-1118
[16] Tan Xiaoyang, Triggs B. Enhanced Local Texture Feature Sets for Face Recognition under Difficult Lighting Conditions. IEEE Trans on Image Processing, 2010, 19(6): 1635-1650
[17] Heikkila M, Pietikainen M, Schmid C. Description of Interest Regions with Local Binary Patterns. Pattern Recognition, 2009, 42(3): 425-436
[18] Kim J K, Park H W. Statistical Textural Features for Detection of Microcalcifications in Digitized Mammograms. IEEE Trans on Me-dical Imaging, 1999, 18(3): 231-238
[19] Massachusetts Institute of Technology. Vision Texture Database[DB/OL]. [2012-07-03].http://vismod.media.mit.edu / vismod/imagery /VisionTexture/vistex.html
[20] Fu Xiaofeng, Wei Wei. Centralized Binary Patterns Embedded with Image Euclidean Distance for Facial Expression Recognition // Proc of the 4th International Conference on Natural Computation. Jinan, China, 2008, IV: 115-119
2013, Vol. 26 
