计算机与数字工程2019，Vol.47Issue(5)：1055-1059,1077,6.DOI:10.3969/j.issn.1672-9722.2019.05.008
一种纹理缺陷特征提取算法
A Texture Defect Feature Extraction Algorithm
摘要
Abstract
In order to extract the fine surface defects of the object with texture more accurately,this paper presents a feature extraction algorithm for texture surface defects based on the second Curvelet transform,gray level co-occurrence matrix and second order oscillation particle swarm optimization. Firstly,the texture defect image is decomposed on different scales and directions,and the high frequency components containing the texture features are found by using the gray level co-occurrence matrix. The high-fre?quency components are extracted and the high-frequency components of the defect details are extracted. Finally,the similarity func?tion is used to find the similarity between the eigenvector of the test sample and the eigenvector of the training sample. According to the similarity value of the test sample,the similarity degree of the test sample is obtained by using the kernel principal component analysis algorithm. Size determines the type of defect for the test sample. The results of this algorithm are more complete and the rec?ognition rate of the defect is higher than that of the non-optimized kernel principal component analysis feature extraction algorithm and the kernel principal component analysis feature extraction algorithm based on clustering.关键词
2代Curvelet变换/灰度共生矩阵/核主成分分析/二阶振荡粒子群优化/特征提取Key words
second Curvelet transform/gray covariance matrix/kernel principal component analysis/second- order oscilla⁃tion particle swarm optimization/defect feature分类
信息技术与安全科学引用本文复制引用
吴焕新,岳晓峰,秦伟洋,张鹏飞..一种纹理缺陷特征提取算法[J].计算机与数字工程,2019,47(5):1055-1059,1077,6.基金项目
吉林省科技攻关计划(编号:20170204010GX)资助. （编号:20170204010GX）
