AGGREGATE IMAGE BASED TEXTURE IDENTIFICATION USING GRAY LEVEL CO-OCCURRENCE PROBABILITY AND BP NEURAL NETWORK  

AGGREGATE IMAGE BASED TEXTURE IDENTIFICATION USING GRAY LEVEL CO-OCCURRENCE PROBABILITY AND BP NEURAL NETWORK

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作  者:Chen Ken Wang Yicong Zhao Pan Larry E. Banta Zhao Xuemei 

机构地区:[1]College of Information Science and Engineering, Ningbo University, Ningbo 315211, China [2]College of Engineering, West Virginia University, WV 26506, USA

出  处:《Journal of Electronics(China)》2009年第3期428-432,共5页电子科学学刊(英文版)

基  金:Funded by Ningbo Natural Science Foundation (No.2006A610016)

摘  要:Classifying the texture of granules in 2D images has aroused manifold research atten-tion for its technical challenges in image processing areas.This letter presents an aggregate texture identification approach by jointly using Gray Level Co-occurrence Probability(GLCP) and BP neural network techniques.First, up to 8 GLCP-associated texture feature parameters are defined and computed, and these consequent parameters next serve as the inputs feeding to the BP neural network to calculate the similarity to any of given aggregate texture type.A finite number of aggregate images of 3 kinds, with each containing specific type of mineral particles, are put to the identification test, experimentally proving the feasibility and robustness of the proposed method.Classifying the texture of granules in 2D images has aroused manifold research attention for its technical challenges in image processing areas. This letter presents an aggregate texture identification approach by jointly using Gray Level Co-occurrence Probability (GLCP) and BP neural network techniques. First, up to 8 GLCP-associated texture feature parameters are defined and computed, and these consequent parameters next serve as the inputs feeding to the BP neural network to calculate the similarity to any of given aggregate texture type. A finite number of aggregate images of 3 kinds, with each containing specific type of mineral particles, are put to the identification test, experimentally proving the feasibility and robustness of the proposed method.

关 键 词:Aggregate image Texture identification Gray Level Co-occurrence Probability(GLCP) BP neural network 

分 类 号:TP183[自动化与计算机技术—控制理论与控制工程] TP391.41[自动化与计算机技术—控制科学与工程]

 

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