西安电子科技大学学报（自然科学版）2011，Vol.38Issue(5)：65-72,8.DOI:10.3969/j.issn.1001-2400.2011.05.011
一种新的布匹瑕疵图像自动检测算法
Novel algorithm for automated detection of fabric defect images
摘要
Abstract
Considering the advantages that decomposition coefficients in the non subsampled Contourlet of fabric images can describe the contour characteristics in a better way, and that they have shift-invariant and multidirection, a novel algorithm for automated detection of fabric defect images is presented. Firstly, the nonsubsampled Contourlet transform (NSCT) is used to perform the sparse representations in multi -scales and multi-directions. On this basis, the optimal sub-bands of NSCT are selected by the cost function, and then the robust descriptions are obtained. Finally, the parameters of defect and nondefect images are timely estimated separately by the Mixture Gaussian Model( MGM), which effectively avoids estimating each defect and reduces the computational complexity evidently. Experimental results show that the proposed algorithm can lead to a better performance than the traditional algorithms in subjective effects and objective evaluation.关键词
瑕疵检测/非下采样Contourlet变换/混合高斯模型/小波变换Key words
defect detection/ nonsubsampled Contourlet transform ( NSCT)/ mixture gaussian model (MGM)/ wavelet transforms分类
信息技术与安全科学引用本文复制引用
崔玲玲,卢朝阳,李静,李益红..一种新的布匹瑕疵图像自动检测算法[J].西安电子科技大学学报（自然科学版）,2011,38(5):65-72,8.基金项目
国家自然科学基金资助项目(60872141) （60872141）
陕西省自然科学基础研究计划资助项目(2009JQ8019) （2009JQ8019）
综合业务网理论及关键技术国家重点实验室基金资助项目(ISN090302) （ISN090302）
西安电子科技大学基础科研业务费资助项目(K50510010007) （K50510010007）
