A set of statistical radial binary patterns for tree species identification based on bark images

[1]  Michal Haindl,et al.  Bark recognition using novel rotationally invariant multispectral textural features , 2019, Pattern Recognit. Lett..

[2]  Vinh Truong Hoang,et al.  Local binary pattern based on image gradient for bark image classification , 2019, International Conference on Signal Processing Systems.

[3]  Laure Tougne,et al.  Efficient Bark Recognition in the Wild , 2019, VISIGRAPP.

[4]  Itheri Yahiaoui,et al.  Bark Identification Using Improved Statistical Radial Binary Patterns , 2018, 2018 International Conference on Content-Based Multimedia Indexing (CBMI).

[5]  Philippe Giguère,et al.  Tree Species Identification from Bark Images Using Convolutional Neural Networks , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[6]  Jiri Matas,et al.  Fine-grained recognition of plants from images , 2017, Plant Methods.

[7]  Itheri Yahiaoui,et al.  Statistical Radial Binary Patterns (SRBP) for Bark Texture Identification , 2017, ACIVS.

[8]  Kai Wang,et al.  Local binary circumferential and radial derivative pattern for texture classification , 2017, Pattern Recognit..

[9]  Laure Tougne,et al.  Bark Recognition to Improve Leaf-based Classification in Didactic Tree Species Identification , 2017, VISIGRAPP.

[10]  Matti Pietikäinen,et al.  Local binary features for texture classification: Taxonomy and experimental study , 2017, Pattern Recognit..

[11]  Matti Pietikäinen,et al.  Extended local binary patterns for face recognition , 2016, Inf. Sci..

[12]  Thanh Phuong Nguyen,et al.  Statistical binary patterns for rotational invariant texture classification , 2016, Neurocomputing.

[13]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[14]  N. Boujemaa,et al.  Semantic-based automatic structuring of leaf images for advanced plant species identification , 2016, Multimedia Tools and Applications.

[15]  Itheri Yahiaoui,et al.  A Comparison of Multi-scale Local Binary Pattern Variants for Bark Image Retrieval , 2015, ACIVS.

[16]  Adriano Bressane,et al.  Pattern recognition in trunk images based on co-occurrence descriptors: A proposal applied to tree species identification , 2015, 2015 Latin America Congress on Computational Intelligence (LA-CCI).

[17]  Guoying Zhao,et al.  BRINT: Binary Rotation Invariant and Noise Tolerant Texture Classification , 2014, IEEE Transactions on Image Processing.

[18]  Xudong Jiang,et al.  LBP-Based Edge-Texture Features for Object Recognition , 2014, IEEE Transactions on Image Processing.

[19]  Rong Xiao,et al.  Pairwise Rotation Invariant Co-Occurrence Local Binary Pattern , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  Alexandru Telea,et al.  International Conference on Computer Vision Theory and Applications (VISAPP) , 2014 .

[21]  D. Hamad,et al.  A new benchmark image test suite for evaluating colour texture classification schemes , 2014, Multimedia Tools and Applications.

[22]  Jiri Matas,et al.  Kernel-mapped histograms of multi-scale LBPs for tree bark recognition , 2013, 2013 28th International Conference on Image and Vision Computing New Zealand (IVCNZ 2013).

[23]  Nozha Boujemaa,et al.  Advanced tree species identification using multiple leaf parts image queries , 2013, 2013 IEEE International Conference on Image Processing.

[24]  Anne Verroust-Blondet,et al.  Plant species recognition using spatial correlation between the leaf margin and the leaf salient points , 2013, 2013 IEEE International Conference on Image Processing.

[25]  Anne Verroust-Blondet,et al.  An android application for leaf-based plant identification , 2013, ICMR.

[26]  Jing Wang,et al.  Fabric defect detection using Gabor filters and defect classification based on LBP and Tamura method , 2013 .

[27]  Wilfried Philips,et al.  The Geometric Local Textural Patterns (GLTP) , 2013, Local Binary Patterns.

[28]  Jun Guo,et al.  Multi-scale Joint Encoding of Local Binary Patterns for Texture and Material Classification , 2013, BMVC.

[29]  Alice Porebski,et al.  Supervised texture classification: color space or texture feature selection? , 2013, Pattern Analysis and Applications.

[30]  Yang Zhao,et al.  Completed Local Binary Count for Rotation Invariant Texture Classification , 2012, IEEE Transactions on Image Processing.

[31]  David A. Clausi,et al.  Sorted random projections for robust rotation-invariant texture classification , 2012, Pattern Recognit..

[32]  C. Romero Bark: A Field Guide to Trees of the Northeast , 2012 .

[33]  Subrahmanyam Murala,et al.  Local Tetra Patterns: A New Feature Descriptor for Content-Based Image Retrieval , 2012, IEEE Transactions on Image Processing.

[34]  Paul W. Fieguth,et al.  Texture Classification from Random Features , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[35]  Paul W. Fieguth,et al.  Extended local binary patterns for texture classification , 2012, Image Vis. Comput..

[36]  Loris Nanni,et al.  Survey on LBP based texture descriptors for image classification , 2012, Expert Syst. Appl..

[37]  Xueming Qian,et al.  PLBP: An effective local binary patterns texture descriptor with pyramid representation , 2011, Pattern Recognit..

[38]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[39]  Andrew Zisserman,et al.  Delving deeper into the whorl of flower segmentation , 2010, Image Vis. Comput..

[40]  Zhenhua Guo,et al.  A Completed Modeling of Local Binary Pattern Operator for Texture Classification , 2010, IEEE Transactions on Image Processing.

[41]  Zhenhua Guo,et al.  Rotation invariant texture classification using LBP variance (LBPV) with global matching , 2010, Pattern Recognit..

[42]  R. Sablatnig,et al.  Automated identification of tree species from images of the bark , leaves and needles , 2010 .

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

[44]  Matti Pietikäinen,et al.  Rotation Invariant Image Description with Local Binary Pattern Histogram Fourier Features , 2009, SCIA.

[45]  Sean White,et al.  Searching the World's Herbaria: A System for Visual Identification of Plant Species , 2008, ECCV.

[46]  Yaniv Taigman,et al.  Descriptor Based Methods in the Wild , 2008 .

[47]  Xianghua Xie,et al.  Handbook of Texture Analysis , 2008 .

[48]  B. K. Julsing,et al.  Face Recognition with Local Binary Patterns , 2012 .

[49]  De-Shuang Huang,et al.  Bark Classification Based on Gabor Filter Features Using RBPNN Neural Network , 2006, ICONIP.

[50]  Zhi-Kai Huang,et al.  Bark Classification Based on Contourlet Filter Features Using RBPNN , 2006, ICIC.

[51]  De-Shuang Huang,et al.  Bark Classification Using RBPNN Based on Gabor Filter in Different Color Space , 2006, 2006 IEEE International Conference on Information Acquisition.

[52]  Wen Gao,et al.  Local Gabor binary pattern histogram sequence (LGBPHS): a novel non-statistical model for face representation and recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[53]  Zheru Chi,et al.  Bark texture feature extraction based on statistical texture analysis , 2004, Proceedings of 2004 International Symposium on Intelligent Multimedia, Video and Speech Processing, 2004..

[54]  Kristin J. Dana,et al.  3D Texture Recognition Using Bidirectional Feature Histograms , 2004, International Journal of Computer Vision.

[55]  Jitendra Malik,et al.  Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons , 2001, International Journal of Computer Vision.

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

[57]  Matti Pietikäinen,et al.  Multi-scale Binary Patterns for Texture Analysis , 2003, SCIA.

[58]  Z. Chi,et al.  Plant species recognition based on bark patterns using novel Gabor filter banks , 2003, International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003.

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

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

[61]  Anil K. Jain,et al.  Texture Analysis , 2018, Handbook of Image Processing and Computer Vision.