森林工程2017，Vol.33Issue(3)：24-27,4.
基于灰度共生矩阵与SOM神经网络的树皮纹理特征识别
Identification of Tree Bark Texture Characteristic Based onGray Co-occurrence Matrix and SOM Neural Network
摘要
Abstract
The extractives of tree bark of Cortex Phellodendri,Fraxinus mandshurica and Catalpa are used as the important source of precious Chinese medicine.The bark is harvested by girdling regeneration technology which ensures the economic needs and also protects the trees.Due to the tree barks of three species are too similar to easily distinguish,it brings the difficult to forestry workers.Therefore it is of practical significance that uses the image processing technology to solve this issue.A total 900 tree bark images of three species,300 per species,were collected.ROI(Region of Interest)image capture and histogram equalization were conducted.The gray level co-occurrence matrix with d of 2,g of 128 and the θ of 0°,45°,90°and 135 ° were constructed.14 characteristic parameters were extracted.8 characteristic parameters were selected effectively through the analysis of digital characteristics.The SOM(Self Organizing Maps)neural network was used to conduct parameters validation for a large number of tree bark images.The parameters set consisting of angular second moment,entropy,moment of inertia,correlation,variance,clustering shadow,and entropy can be used to effectively distinguish three tree species with the recognition of 83.33%.The method studied in this paper is capable to well distinguish three trees species of Cortex Phellodendri,Fraxinus mandshurica and Catalpa.关键词
树皮纹理/灰度共生矩阵/SOM神经网络Key words
tree bark texture/gray co-occurrence matrix/SOM neural network分类
农业科技引用本文复制引用
李可心,戚大伟,牟洪波,倪海明..基于灰度共生矩阵与SOM神经网络的树皮纹理特征识别[J].森林工程,2017,33(3):24-27,4.基金项目
国家自然科学基金项目(31570712) （31570712）
黑龙江省教育厅科学技术研究项目(12543019) （12543019）
黑龙江省自然科学基金项目(C201338) （C201338）
高校科研基金项目(2572014CB30) （2572014CB30）
中央高校基本科研业务费专项资金资助项目(2572016AB26) （2572016AB26）
