2.845

2023影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

局部二值模式方法研究与展望

宋克臣 颜云辉 陈文辉 张旭

宋克臣, 颜云辉, 陈文辉, 张旭. 局部二值模式方法研究与展望. 自动化学报, 2013, 39(6): 730-744. doi: 10.3724/SP.J.1004.2013.00730
引用本文: 宋克臣, 颜云辉, 陈文辉, 张旭. 局部二值模式方法研究与展望. 自动化学报, 2013, 39(6): 730-744. doi: 10.3724/SP.J.1004.2013.00730
SONG Ke-Chen, YAN Yun-Hui, CHEN Wen-Hui, ZHANG Xu. Research and Perspective on Local Binary Pattern. ACTA AUTOMATICA SINICA, 2013, 39(6): 730-744. doi: 10.3724/SP.J.1004.2013.00730
Citation: SONG Ke-Chen, YAN Yun-Hui, CHEN Wen-Hui, ZHANG Xu. Research and Perspective on Local Binary Pattern. ACTA AUTOMATICA SINICA, 2013, 39(6): 730-744. doi: 10.3724/SP.J.1004.2013.00730

局部二值模式方法研究与展望

doi: 10.3724/SP.J.1004.2013.00730
基金项目: 

中央高校基本科研业务费专项资金(N120603003)资助

详细信息
    通讯作者:

    宋克臣

Research and Perspective on Local Binary Pattern

Funds: 

Supported by Fundamental Research Funds for the Central Universities(N120603003)

  • 摘要: 针对当前局部二值模式(Local binary pattern, LBP)方法表现出的理论和实际应用价值, 系统综述了在纹理分析和分类、人脸分析和识别以及其他检测与应用中的各种LBP 方法.首先, 简要概述了LBP方法的原理, 主要分析了LBP 方法中的阈值操作并介绍了统一模式和旋转不变性模式.其次, 分别对纹理分析和分类中的LBP方法、人脸分析和识别中的LBP方法以及其他检测与应用中的LBP方法等三个方面进行了详细的梳理和评述.最后, 分析了LBP方法在应用中依旧存在的重要问题并指出了未来的研究方向.
  • [1] Ojala T, Pietikäinen M, Harwood D. A comparative study of texture measures with classification based on featured distributions. Pattern Recognition, 1996, 29(1): 51-59
    [2] Pietikäinen M, Ojala T, Xu Z. Rotation-invariant texture classification using feature distributions. Pattern Recognition, 2000, 33(1): 43-52
    [3] Ojala T, Valkealahti K, Oja E, Pietikäinen M. Texture discrimination with multidimensional distributions of signed gray-level differences. Pattern Recognition, 2001, 34(3): 727-739
    [4] Ojala T, Pietikäinen M, Mäenpää T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(7): 971-987
    [5] Pietikäinen M, Hadid A, Zhao G Y, Ahonen T. Computer Vision Using Local Binary Patterns. Berlin: Springer-Verlag, 2011. 193-202
    [6] Hafiane A, Seetharaman G, Zavidovique B. Median binary pattern for textures classification. In: Proceedings of the 2007 International Conference on Image Analysis and Recognition. Montreal, Canada: Springer, 2007. 387-398
    [7] Guo Z H, Zhang L, Zhang D, Zhang S. Rotation invariant texture classification using adaptive LBP with directional statistical features. In: Proceedings of the 17th IEEE International Conference on Image Processing. Hong Kong, China: IEEE, 2010. 285-288
    [8] Varma M, Zisserman A. A statistical approach to material classification using image patch exemplars. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31(11): 2032-2047
    [9] Guo Z H, Zhang L, Zhang D. A completed modeling of local binary pattern operator for texture classification. IEEE Transactions on Image Processing, 2010, 19(6): 1657-1663
    [10] Guo Z H, Zhang L, Zhang D. Rotation invariant texture classification using LBP variance (LBPV) with global matching. Pattern Recognition, 2010, 43(3): 706-719
    [11] He C, Ahonen T, Pietikäinen M. A Bayesian local binary pattern texture descriptor. In: Proceedings of the 19th International Conference on Pattern Recognition. Tampa, USA: IEEE, 2008. 1-4
    [12] Brodatz P. Textures: A Photographic Album for Artists and Designers. New York: Dover Publications, 1966. 1-112
    [13] Liao S, Law M W K, Chung A C S. Dominant local binary patterns for texture classification. IEEE Transactions on Image Processing, 2009, 18(5): 1107-1118
    [14] Ojala T, Mäenpää T, Pietikäinen M, Viertola J, Kyllönen J, Huovinen S. Outex-new framework for empirical evaluation of texture analysis algorithms. In: Proceedings of the 16th International Conference on Pattern Recognition. Quebec, Canada: IEEE, 2002. 701-706
    [15] Nanni L, Lumini A, Brahnam S. Survey on LBP based texture descriptors for image classification. Expert Systems with Applications, 2012, 39(3): 3634-3641
    [16] Mäenpää T, Ojala T, Pietikäinen M, Soriano M. Robust texture classification by subsets of local binary patterns. In: Proceedings of the 2000 International Conference on Pattern Recognition. Barcelona, Spain: IEEE, 2000. 947-950
    [17] Mäenpää T, Pietikäinen M. Multi-scale binary patterns for texture analysis. In: Proceedings of the 13th Scandinavian Conference on Image Analysis. Lecture Notes in Computer Science. Berlin, Germany: Springer, 2003. 885-892
    [18] Raja Y, Gong S G. Sparse multiscale local binary patterns. In: Proceedings of the 2006 British Machine Vision Conference. Edinburgh, UK: BMVA, 2006. 1-10
    [19] He Y G, Sang N, Gao C X. Pyramid-based multi-structure local binary pattern for texture classification. In: Proceedings of the 10th Asian Conference on Computer Vision. Berlin, Heidelberg: Springer, 2011. 133-144
    [20] Ahonen T, Pietikäinen M. Soft histograms for local binary patterns. In: Proceedings of the 2007 Finnish Signal Processing Symposium. Oulu, Finland: FINSIG, 2007. 1-4
    [21] Iakovidis D K, Keramidas E, Maroulis D. Fuzzy local binary patterns for ultrasound texture characterization. In: Proceedings of the 5th International Conference on Image Analysis and Recognition. Berlin, Heidelberg: Springer, 2008. 750-759
    [22] Zhang L, Zhang L, Guo Z H, Zhang D. Monogenic-LBP: a new approach for rotation invariant texture classification. In: Proceedings of the 17th International Conference on Image Processing. Hong Kong, China: IEEE, 2010. 2677-2680
    [23] Zhou H, Wang R S, Wang C. A novel extended local-binary-pattern operator for texture analysis. Information Sciences, 2008, 178(22): 4314-4325
    [24] Liu L, Zhao L J, Long Y L, Kuang G Y, Fieguth P. Extended local binary patterns for texture classification. Image and Vision Computing, 2012, 30(2): 86-99
    [25] Khellah F M. Texture classification using dominant neighborhood structure. IEEE Transactions on Image Processing, 2011, 20(11): 3270-3279
    [26] Guo Y M, Zhao G Y, Pietikäinen M. Discriminative features for texture description. Pattern Recognition, 2012, 45(10): 3834-3843
    [27] Guo Y, Zhao G, Pietikäinen M, Xu Z. Descriptor learning based on Fisher separation criterion for texture classification. In: Proceedings of the 2011 Asian Conference on Computer Vision. Queenstown, New Zealand: Springer, 2011. 185-198
    [28] Zhao Y, Huang D S, Jia W. Completed local binary count for rotation invariant texture classification. IEEE Transactions on Image Processing, 2012, 21(10): 4492-4497
    [29] Fathi A, Naghsh-Nilchi A R. Noise tolerant local binary pattern operator for efficient texture analysis. Pattern Recognition Letters, 2012, 33(9): 1093-1100
    [30] Mäenpää T, Pietikäinen M. Classification with color and texture: jointly or separately? Pattern Recognition, 2004, 37(8): 1629-1640
    [31] Pietikäinen M, Mäenpää T, Viertola J. Color texture classification with color histograms and local binary patterns. In: Proceedings of the 2008 International Workshop on Texture Analysis and Synthesis. Copenhagen, Denmark: IWTAS, 2002. 109-112
    [32] Porebski A, Vandenbroucke N, Macaire L. Haralick feature extraction from LBP images for color texture classification. In: Proceedings of the 2008 International Workshops on Image Processing Theory, Tools and Applications. Sousse, Tunisia: IEEE, 2008. 1-8
    [33] Zhang J, Liang J M, Zhao H. Local energy pattern for texture classification using self-adaptive quantization thresholds. IEEE Transactions on Image Processing, 2013, 22(1): 31-42
    [34] Zhao G Y, Ahonen T, Matas J, Pietikäinen M. Rotation-invariant image and video description with local binary pattern features. IEEE Transactions on Image Processing, 2012, 21(4): 1465-1477
    [35] Ojansivu V, Heikkilä J. Blur insensitive texture classification using local phase quantization. In: Proceedings of the 2008 International Conference on Image and Signal Processing. Cherbourg-Octeville, France: Springer, 2008. 236-243
    [36] Lategahn H, Gross S, Stehle T, Aach T. Texture classification by modeling joint distributions of local patterns with Gaussian mixtures. IEEE Transactions on Image Processing, 2010, 19(6): 1548-1557
    [37] Chen J, Shan S G, He C, Zhao G Y, Pietikäinen M, Chen X L, Gao W. WLD: a robust local image descriptor. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(9): 1705-1720
    [38] Liu L, Fieguth P, Clausi D, Kuang G Y. Sorted random projections for robust rotation-invariant texture classification. Pattern Recognition, 2012, 45(6): 2405-2418
    [39] Liao S, Chung A C S. Face recognition by using elongated local binary patterns with average maximum distance gradient magnitude. In: Proceedings of the 8th Asian Conference on Computer Vision. Tokyo, Japan: Springer, 2007. 672-679
    [40] Jin H L, Liu Q S, Lu H Q, Tong X F. Face detection using improved LBP under Bayesian framework. In: Proceedings of the 3rd International Conference on Image and Graphics. Hong Kong, China: IEEE, 2004. 306-309
    [41] Petpon A, Srisuk S. Face recognition with local line binary pattern. In: Proceedings of the 5th International Conference on Image and Graphics. Xi'an, China: IEEE, 2010. 533-539
    [42] Tan X Y, Triggs B. Enhanced local texture feature sets for face recognition under difficult lighting conditions. In: Proceedings of the 3rd International Conference on Analysis and Modeling of Faces and Gestures. Rio de Janeiro, Brazil: Springer, 2007. 168-182
    [43] Liao S C, Zhu X X, Lei Z, Zhang L, Li S Z. Learning multi-scale block local binary patterns for face recognition. In: Proceedings of the 2007 International Conference on Biometrics. Seoul, South Korea: Springer, 2007. 828-837
    [44] Zhang L, Chu R F, Xiang S M, Liao S C, Li S Z. Face detection based on multi-block LBP representation. In: Proceedings of the 2007 International Conference on Advances in Biometrics. Seoul, South Korea: Springer, 2007. 11-18
    [45] Wolf L, Hassner T, Taigman Y. Descriptor based methods in the wild. In: Proceedings of the 2008 European Conference on Computer Vision Workshop on Faces in Real-Life Images. Marseille, France: Springer, 2008. 1-14
    [46] Samaria F S, Harter A C. Parameterisation of a stochastic model for human face identification. In: Proceedings of the 2nd IEEE Workshop on Applications of Computer Vision. Sarasota, USA: IEEE, 1994. 138-142
    [47] Belhumeur P N, Hespanha J P, Kriegman D J. Eigenfaces vs. Fisherfaces: recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(7): 711-720
    [48] Phillips P J, Wechsler H, Huang J, Rauss P J. The FERET database and evaluation procedure for face-recognition algorithms. Image and Vision Computing, 1998, 16(5): 295-306
    [49] Phillips P J, Flynn P J, Scruggs T, Bowyer K W, Chang J, Hoffman K, Marques J, Jaesik M, Worek W. Overview of the face recognition grand challenge. In: Proceedings of the 2005 IEEE Conference on Computer Vision and Pattern Recognition. San Diego, USA: IEEE, 2005. 947-954
    [50] Huang G B, Ramesh M, Berg T, Learned-Miller E. Labeled Faces in the Wild: a Database for Studying Face Recognition in Unconstrained Environments, Technical Report, Department of Computer Science, University of Massachusetts, USA, 2007
    [51] Huang D, Shan C F, Ardabilian M, Wang Y H, Chen L M. Local binary patterns and its application to facial image analysis: a survey. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 2011, 41(6): 765-781
    [52] Chan C H, Kittler J V, Messer K. Multispectral local binary pattern histogram for component-based color face verification. In: Proceedings of the 2007 IEEE Conference on Biometrics: Theory, Applications and Systems. Crystal City, USA: IEEE, 2007. 1-7
    [53] Chan C H, Kittler J, Messer K. Multi-scale local binary pattern histograms for face recognition. In: Proceedings of the 2007 International Conference on Biometrics. Seoul, South Korea: Springer, 2007. 809-818
    [54] Zhang W C, Shan S G, Gao W, Chen X L, Zhang H M. Local gabor binary pattern histogram sequence (LGBPHS): a novel non-statistical model for face representation and recognition. In: Proceedings of the 10th International Conference on Computer Vision. Beijing, China: IEEE, 2005. 786-791
    [55] Tan X Y, Triggs B. Fusing Gabor and LBP feature sets for kernel-based face recognition. In: Proceedings of the 2007 Corference on Analysis and Modeling of Faces and Gestures. Rio de Janeiro, Brazil: Springer, 2007. 235-249
    [56] Shan S G, Zhang W C, Su Y, Chen X L, Gao W. Ensemble of piecewise FDA based on spatial histograms of local (Gabor) binary patterns for face recognition. In: Proceedings of the 18th International Conference on Pattern Recognition. Hong Kong, China: IEEE, 2006. 606-609
    [57] Maturana D, Soto A, Mery D. Face recognition with decision tree-based local binary patterns. In: Proceedings of the 2011 Asian Conference on Computer Vision. Queenstown, New Zealand: Springer, 2011. 618-629
    [58] Lahdenoja O, Laiho M, Paasio A. Reducing the feature vector length in local binary pattern based face recognition. In: Proceedings of the 2005 International Conference on Image Processing. Genoa, Italy: IEEE, 2005. 914-917
    [59] Zhang B C, Gao Y S, Zhao S Q, Liu J Z. Local derivative pattern versus local binary pattern: face recognition with high-order local pattern descriptor. IEEE Transactions on Image Processing, 2010, 19(2): 533-544
    [60] Shan C F, Gritti T. Learning discriminative LBP-histogram bins for facial expression recognition. In: Proceedings of the 2008 British Machine Vision Conference. Leeds, UK: BMVC, 2008. 1-10
    [61] Ho An K, Chung M. Cognitive face analysis system for future interactive TV. IEEE Transactions on Consumer Electronics, 2009, 55(4): 2271-2279
    [62] Yan S Y, Shan S G, Chen X, Gao W. Locally assembled binary (LAB) feature with feature-centric cascade for fast and accurate face detection. In: Proceedings of the 2008 IEEE Conference on Computer Vision and Pattern Recognition. Anchorage, USA: IEEE, 2008. 1-7
    [63] Roy A, Marcel S. Haar local binary pattern feature for fast illumination invariant face detection. In: Proceedings of the 2009 British Machine Vision Conference. London, UK: BMVC, 2009
    [64] Yang H, Wang Y D. A LBP-based face recognition method with Hamming distance constraint. In: Proceedings of the 4th International Conference on Image and Graphics. Sichuan, China: IEEE, 2007. 645-649
    [65] Fu X F, Wei W. Centralized binary patterns embedded with image Euclidean distance for facial expression recognition. In: Proceedings of the 4th International Conference on Natural Computation. Ji'nan, China: IEEE, 2008. 115-119
    [66] Zhang G C, Huang X S, Li S Z, Wang Y S, Wu X H. Boosting local binary pattern (LBP)-based face recognition. In: Proceedings of the 2005 Advances in Biometric Person Authentication. Beijing, China: Springer, 2005. 179-186
    [67] Mu Y D, Yan S C, Liu Y, Huang T, Zhou B F. Discriminative local binary patterns for human detection in personal album. In: Proceedings of the 2005 IEEE Conference on Computer Vision and Pattern Recognition. Anchorage, USA: IEEE, 2008. 1-8
    [68] Dalal N, Triggs B. Histograms of oriented gradients for human detection. In: Proceedings of the 2005 IEEE Conference on Computer Vision and Pattern Recognition. San Diego, USA: IEEE, 2005. 886-893
    [69] Wang X Y, Han T X, Yan S C. An hog-lbp human detector with partial occlusion handling. In: Proceedings of the 2009 International Conference on Computer Vision. Kyoto, Japan: IEEE, 2009. 32-39
    [70] Trefny J, Matas J. Extended set of local binary patterns for rapid object detection. In: Proceedings of the 2010 Computer Vision Winter Workshop. Nove Hrady, Czech Republic: CVWW, 2010. 1-7
    [71] Agarwal S, Awan A, Roth D. Learning to detect objects in images via a sparse, part-based representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(11): 1475-1490
    [72] Heikkilä M, Pietikäinen M, Schmid C. Description of interest regions with local binary patterns. Pattern Recognition, 2009, 42(3): 425-436
    [73] Zhao G Y, Pietikäinen M. Dynamic texture recognition using local binary patterns with an application to facial expressions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, 29(6): 915-928
    [74] Kanade T, Cohn J F, Tian Y L. Comprehensive database for facial expression analysis. In: Proceedings of the 4th International Conference on Automatic Face and Gesture Recognition. Grenoble, France: IEEE, 2000. 46-53
    [75] Heikkilä M, Pietikäinen M. A texture-based method for modeling the background and detecting moving objects. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28(4): 657-662
    [76] Heikkilä M, Pietikäinen M, Heikkilä J. A texture-based method for detecting moving objects. In: Proceedings of the 2004 British Machine Vision Conference. London, UK: BMVC, 2004. 187-196
    [77] Toyama K, Krumm J, Brumitt B, Meyers B. Wallflower: principles and practice of background maintenance. In: Proceedings of the 1999 IEEE International Conference on Computer Vision. Kerkyra, Greece: IEEE, 1999. 255-261
    [78] Takala V, Pietikäinen, M. Multi-object tracking using color, texture and motion. In: Proceedings of the 2007 IEEE International Workshop on Visual Surveillance. Minneapolis, USA: IEEE, 2007. 1-7
    [79] Yao J, Odobez J M. Multi-layer background subtraction based on color and texture. In: Proceedings of the 2007 IEEE Conference on Computer Vision and Pattern Recognition. Minneapolis, USA: IEEE, 2007. 3658-3665
    [80] Liao S C, Zhao G Y, Kellokumpu V, Pietikäinen M, Li S Z. Modeling pixel process with scale invariant local patterns for background subtraction in complex scenes. In: Proceedings of the 2010 IEEE Conference on Computer Vision and Pattern Recognition. San Francisco, USA: IEEE, 2010. 1301-1306
    [81] Kellokumpu V, Zhao G Y, Pietikäinen M. Human activity recognition using a dynamic texture based method. In: Proceedings of the 2008 British Machine Vision Conference. London, UK: BMVC, 2008. 1-10
    [82] Kellokumpu V, Zhao G Y, Pietikäinen M. Texture based description of movements for activity analysis. In: Proceedings of the 2008 International Conference on Computer Vision Theory and Applications. Funchal, Portugal: VISAPP, 2008. 206-213
    [83] Kellokumpu V, Zhao G Y, Li S Z, Pietikäinen M. Dynamic texture based gait recognition. In: Proceedings of the 3rd International Conference on Advances in Biometrics. Alghero, Italy: Springer, 2009. 1000-1009
    [84] Kellokumpu V, Zhao G Y, Pietikäinen M. Recognition of human actions using texture descriptors. Machine Vision and Applications, 2011, 22(5): 767-780
    [85] Costa Y M G, Oliveira L S, Koerich A L, Gouyon F, Martins J G. Music genre classification using LBP textural features. Signal Processing, 2012, 92(11): 2723-2737
    [86] Caputo B, Hayman E, Mallikarjuna P. Class-specific material categorisation. In: Proceedings of the 2005 IEEE International Conference on Computer Vision. Beijing, China: IEEE, 2005. 1597-1604
    [87] Caputo B, Hayman E, Fritz M, Eklundh J O. Classifying materials in the real world. Image and Vision Computing, 2010, 28(1): 150-163
  • 加载中
计量
  • 文章访问数:  3639
  • HTML全文浏览量:  118
  • PDF下载量:  5124
  • 被引次数: 0
出版历程
  • 收稿日期:  2012-07-04
  • 修回日期:  2012-11-07
  • 刊出日期:  2013-06-20

目录

    /

    返回文章
    返回