激光与光电子学进展, 2018, 55 (7): 071501, 网络出版: 2018-07-20   

基于最优Gabor滤波器的牛仔布缺陷检测 下载: 702次

Denim Defect Detection Based on Optimal Gabor Filter
作者单位
西安工程大学电子信息学院, 陕西 西安 710048
摘要
针对牛仔布人工检测慢,误检、漏检率高的问题,提出一种采用最优Gabor滤波器的牛仔布缺陷自动检测算法。首先,对正常的牛仔布图像构造任意的二维Gabor滤波器,同时,采用改进的差分进化算法优化Gabor滤波器参数,得到与正常牛仔布纹理最匹配的参数;然后,根据最优参数构造Gabor滤波器,对待检测图像进行卷积处理,得到特征图像,再结合阈值操作得到初步检测结果;最后,使用矩形框与局部大津法分割出精确的缺陷区域。实验结果表明:该算法能够实现牛仔布的缺陷检测,具有学习时间短、稳健性强和准确率高的特点。
Abstract
Aiming at the problems of slow speed, high rates of false detection and miss detection in denim artificial operation, we propose an automatic defect detection algorithm of denim by using the optimal Gabor filter. Firstly, an arbitrary two-dimensional Gabor filter is constructed for the normal denim image. Meanwhile an improved differential evolution algorithm is used to optimize the parameters of Gabor filter to get the best match with the normal denim texture. Secondly, the Gabor filter is constructed according to the optimal parameters, following which, an operation of convolution is applied to the image to be detected to obtain the corresponding feature image. Then, the initial detection result is obtained by combination with the threshold operation. Finally, we use the rectangular box and the local Otsu method to separate the exact defect area. Experimental results show that the proposed algorithm can better detect the denim defects with short learning time, strong robustness and high accuracy.

王清晨, 景军锋, 张蕾, 王晓华, 李鹏飞. 基于最优Gabor滤波器的牛仔布缺陷检测[J]. 激光与光电子学进展, 2018, 55(7): 071501. Wang Qingchen, Jing Junfeng, Zhang Lei, Wang Xiaohua, Li Pengfei. Denim Defect Detection Based on Optimal Gabor Filter[J]. Laser & Optoelectronics Progress, 2018, 55(7): 071501.

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