Local directional derivative pattern for rotation invariant texture classification

Local binary pattern (LBP) is a simple and efficient operator to describe local image pattern. It could be regarded as a binary representation of 1st order derivative between the central and its neighbors. Based on LBP definition, in this paper, a framework of local directional derivative pattern (LDDP) is proposed which could represent high order directional derivative feature, and LBP is a special case of LDDP. Under the proposed framework, like traditional LBP, rotation invariance could be easily defined. As different order derivative information contains complementary features, better recognition accuracy could be achieved by combining different order LDDPs which is validated by two large public texture databases, Outex and CUReT.

[1]  Jian Fan,et al.  Texture Classification by Wavelet Packet Signatures , 1993, MVA.

[2]  Shree K. Nayar,et al.  Reflectance and texture of real-world surfaces , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[3]  David Zhang,et al.  Texture classification via patch-based sparse texton learning , 2010, 2010 IEEE International Conference on Image Processing.

[4]  Matti Pietikäinen,et al.  Outex - new framework for empirical evaluation of texture analysis algorithms , 2002, Object recognition supported by user interaction for service robots.

[5]  C. H. Chen,et al.  Handbook of Pattern Recognition and Computer Vision , 1993 .

[6]  Michael Unser,et al.  Texture classification and segmentation using wavelet frames , 1995, IEEE Trans. Image Process..

[7]  Matti Pietikäinen,et al.  View-based recognition of real-world textures , 2004, Pattern Recognit..

[8]  Rangasami L. Kashyap,et al.  A Model-Based Method for Rotation Invariant Texture Classification , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Andrew Zisserman,et al.  A Statistical Approach to Material Classification Using Image Patch Exemplars , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Joachim M. Buhmann,et al.  Empirical Evaluation of Dissimilarity Measures for Color and Texture , 2001, Comput. Vis. Image Underst..

[11]  D. He,et al.  Evaluation of textural and multipolarization radar features for crop classification , 1995, IEEE Trans. Geosci. Remote. Sens..

[12]  Matti Pietikäinen,et al.  Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Ajai Jain,et al.  The Handbook of Pattern Recognition and Computer Vision , 1993 .

[14]  Kee Tung. Wong,et al.  Texture features for image classification and retrieval. , 2002 .

[15]  David R. Bull,et al.  Projective image restoration using sparsity regularization , 2013, 2013 IEEE International Conference on Image Processing.

[16]  Byung-Woo Hong,et al.  Locally Rotation, Contrast, and Scale Invariant Descriptors for Texture Analysis , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  LinLin Shen,et al.  Directional binary code with application to PolyU near-infrared face database , 2010, Pattern Recognit. Lett..

[18]  Cordelia Schmid,et al.  A sparse texture representation using local affine regions , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  A. Kundu,et al.  Rotation and Gray Scale Transform Invariant Texture Identification using Wavelet Decomposition and Hidden Markov Model , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  B. S. Manjunath,et al.  Texture Features for Browsing and Retrieval of Image Data , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Anil K. Jain,et al.  Texture classification and segmentation using multiresolution simultaneous autoregressive models , 1992, Pattern Recognit..

[22]  Andrew Zisserman,et al.  A Statistical Approach to Texture Classification from Single Images , 2005, International Journal of Computer Vision.

[23]  Marko Heikkilä,et al.  Description of interest regions with local binary patterns , 2009, Pattern Recognit..

[24]  Andrew Zisserman,et al.  Unifying statistical texture classification frameworks , 2004, Image Vis. Comput..

[25]  C.-C. Jay Kuo,et al.  Texture analysis and classification with tree-structured wavelet transform , 1993, IEEE Trans. Image Process..

[26]  Matti Pietikäinen,et al.  Face Description with Local Binary Patterns: Application to Face Recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[27]  R. Porter,et al.  Robust rotation-invariant texture classification: wavelet, Gabor filter and GMRF based schemes , 1997 .

[28]  Wen-Rong Wu,et al.  Rotation and gray-scale transform-invariant texture classification using spiral resampling, subband decomposition, and hidden Markov model , 1996, IEEE Trans. Image Process..

[29]  H. Arof,et al.  Circular neighbourhood and 1-D DFT features for texture classification and segmentation , 1998 .

[30]  Xiaoyang Tan,et al.  Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions , 2007, IEEE Transactions on Image Processing.

[31]  Andrew Zisserman,et al.  A Statistical Approach to Texture Classification from Single Images , 2004, International Journal of Computer Vision.

[32]  Jing-Yu Yang,et al.  A novel method for Fisher discriminant analysis , 2004, Pattern Recognit..

[33]  Zhigang Fan,et al.  Automated Inspection of Textile Fabrics Using Textural Models , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  Yong Xu,et al.  Viewpoint Invariant Texture Description Using Fractal Analysis , 2009, International Journal of Computer Vision.

[35]  Stan Z. Li,et al.  Shape localization based on statistical method using extended local binary pattern , 2004, Third International Conference on Image and Graphics (ICIG'04).

[36]  Kevin W. Bowyer,et al.  Combination of multiple classifiers using local accuracy estimates , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[37]  Aapo Hyvärinen,et al.  Survey on Independent Component Analysis , 1999 .

[38]  Baochang Zhang,et al.  Local Derivative Pattern Versus Local Binary Pattern: Face Recognition With High-Order Local Pattern Descriptor , 2010, IEEE Transactions on Image Processing.

[39]  Matti Pietikäinen,et al.  Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[40]  Wilson S. Geisler,et al.  Multichannel Texture Analysis Using Localized Spatial Filters , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[41]  Jiri Matas,et al.  On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[42]  Wen-Rong Wu,et al.  Correction To "rotation And Gray-scale Transform-invariant Texture Classification Using Spiral Resampling, Subband Decomposition, And Hidden Markov Model" , 1996, IEEE Trans. Image Process..

[43]  Qiang Ji,et al.  Texture analysis for classification of cervix lesions , 2000, IEEE Transactions on Medical Imaging.

[44]  Shu Liao,et al.  Dominant Local Binary Patterns for Texture Classification , 2009, IEEE Transactions on Image Processing.