Implementation of Leaf Image Recognition System Based on LBP and B/S Framework

Plant identification system is on the basis of the previous, through continuous optimizing all aspects of the algorithm to improve efficiency and accuracy of the algorithm. For feature extraction, since the local binary pattern was proposed in the past decades, it has been widely used in computer vision to describe the feature for image classification such as image recognition, motion detection and medical image analysis. According to accuracy of the descriptor always fluctuates with different samples, some improved pattern of LBP has been presented in papers. Complete Local Binary Pattern (CLBP) is an optimized version which set an additional magnitude value to local differences. This paper shows extensive experiments of implement the LBP derivatives for plants texture identification. Finally realize an online system to identify what kind of the plant image user uploaded based on LBP descriptor.

[1]  Anders Krogh,et al.  Neural Network Ensembles, Cross Validation, and Active Learning , 1994, NIPS.

[2]  D. Coomans,et al.  Alternative k-nearest neighbour rules in supervised pattern recognition : Part 1. k-Nearest neighbour classification by using alternative voting rules , 1982 .

[3]  Shuicheng Yan,et al.  An HOG-LBP human detector with partial occlusion handling , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[4]  Jian-Gang Wang,et al.  Age categorization via ECOC with fused gabor and LBP features , 2009, 2009 Workshop on Applications of Computer Vision (WACV).

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

[6]  D.-S. Huang,et al.  Radial Basis Probabilistic Neural Networks: Model and Application , 1999, Int. J. Pattern Recognit. Artif. Intell..

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

[8]  Ge Yu-rong.  Texture feature recognition based on Contourlet transform and support vector machine , 2013 .

[9]  De-Shuang Huang,et al.  Human face recognition based on multi-features using neural networks committee , 2004, Pattern Recognit. Lett..

[10]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[11]  De-Shuang Huang,et al.  Locally linear discriminant embedding: An efficient method for face recognition , 2008, Pattern Recognit..

[12]  Pat Morin,et al.  Output-Sensitive Algorithms for Computing Nearest-Neighbour Decision Boundaries , 2005, Discret. Comput. Geom..

[13]  Hedieh Sajedi,et al.  A Contourlet-Based Face Detection Method in Color Images , 2007, 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System.

[14]  Zhu Xiangbin,et al.  Texture classification based on contourlet and support vector machines , 2009, 2009 ISECS International Colloquium on Computing, Communication, Control, and Management.

[15]  Li Shang,et al.  Palmprint recognition using FastICA algorithm and radial basis probabilistic neural network , 2006, Neurocomputing.

[16]  Jiayi Wang,et al.  Texture feature recognition based on Contourlet transform and support vector machine: Texture feature recognition based on Contourlet transform and support vector machine , 2013 .

[18]  Xiaofeng Wang,et al.  A Novel Density-Based Clustering Framework by Using Level Set Method , 2009, IEEE Transactions on Knowledge and Data Engineering.

[19]  Minh N. Do,et al.  Ieee Transactions on Image Processing the Contourlet Transform: an Efficient Directional Multiresolution Image Representation , 2022 .

[20]  Saeid Rahati,et al.  Vehicle Recognition Using Contourlet Transform and SVM , 2008, Fifth International Conference on Information Technology: New Generations (itng 2008).

[21]  De-Shuang Huang,et al.  A Neural Root Finder of Polynomials Based on Root Moments , 2004, Neural Computation.

[22]  De-Shuang Huang,et al.  Normalized Feature Vectors: A Novel Alignment-Free Sequence Comparison Method Based on the Numbers of Adjacent Amino Acids , 2013, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

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

[24]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[25]  Xiaofeng Wang,et al.  An efficient local Chan-Vese model for image segmentation , 2010, Pattern Recognit..

[26]  De-Shuang Huang,et al.  A General CPL-AdS Methodology for Fixing Dynamic Parameters in Dual Environments , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[27]  Yoav Freund,et al.  Experiments with a New Boosting Algorithm , 1996, ICML.

[28]  De-Shuang Huang,et al.  A constructive approach for finding arbitrary roots of polynomials by neural networks , 2004, IEEE Transactions on Neural Networks.

[29]  Xiaoyang Tan,et al.  Fusing Gabor and LBP Feature Sets for Kernel-Based Face Recognition , 2007, AMFG.

[30]  Desire L. Massart,et al.  Alternative k-nearest neighbour rules in supervised pattern recognition : Part 2. Probabilistic classification on the basis of the kNN method modified for direct density estimation , 1982 .

[31]  Gaines E. Miles,et al.  MACHINE VISION AND IMAGE PROCESSING FOR PLANT IDENTIFICATION. , 1986 .

[32]  De-Shuang Huang,et al.  A Constructive Hybrid Structure Optimization Methodology for Radial Basis Probabilistic Neural Networks , 2008, IEEE Transactions on Neural Networks.

[33]  Cheng Wang,et al.  A novel extended local-binary-pattern operator for texture analysis , 2008, Inf. Sci..

[34]  Ahmed Bouridane,et al.  Contourlet-Based Feature Extraction with PCA for Face Recognition , 2008, 2008 NASA/ESA Conference on Adaptive Hardware and Systems.

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

[36]  Zhe Liu,et al.  SAR Image Segmentation Using Contourlet and Support Vector Machine , 2009, 2009 Fifth International Conference on Natural Computation.