[1]蒋洁琦,杨 庚,刘沛东,等.表面弱边缘瑕疵检测算法及应用[J].计算机技术与发展,2019,29(05):142-147.[doi:10. 3969 / j. issn. 1673-629X. 2019. 05. 030]
　JIANG Jie-qi,YANG Geng,LIU Pei-dong,et al.Surface Weak Edge Flaw Detection Algorithm and Its Application[J].,2019,29(05):142-147.[doi:10. 3969 / j. issn. 1673-629X. 2019. 05. 030]
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表面弱边缘瑕疵检测算法及应用()

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年05期
页码:
142-147
栏目:
应用开发研究
出版日期:
2019-05-10

文章信息/Info

Title:
Surface Weak Edge Flaw Detection Algorithm and Its Application
文章编号:
1673-629X(2019)05-0142-06
作者:
蒋洁琦1; 杨 庚1; 刘沛东2; 钱 晨3
1. 南京邮电大学 计算机学院、软件学院,江苏 南京 210046;2. 江苏亨通光电有限公司,江苏 苏州 215200;3. 南京邮电大学 光电学院,江苏 南京 210046
Author(s):
JIANG Jie-qi1; YANG Geng1; LIU Pei-dong2; QIAN Chen3
1. School of Computer Science and Software,Nanjing University of Posts and Telecommunications, Nanjing 210046,China;2. Jiangsu Hengtong Au Optronics Co,Suzhou 215200,China;3. School of Optoelectronic Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210046,China
关键词:
图像处理; 弱边缘; 表面瑕疵检测; Scharr 算子; 边缘检测
Keywords:
image processing; weak edge; surface defect detection; Scharr operator; edge detection
分类号:
TP391. 41
DOI:
10. 3969 / j. issn. 1673-629X. 2019. 05. 030
摘要:
工业环境中,产品表面质量是产品质量的重要组成部分,也是商品商业价值的重要保障。 产品表面瑕疵由于受到光源、光照方式等因素的影响,容易形成灰度变化相对缓慢的过渡边缘即弱边缘。 在工业生产中,弱边缘瑕疵由于其灰度缓慢变化,所以相对强边缘瑕疵较难被检测出。 针对这一问题,提出了一种有效检测弱边缘瑕疵的方法。 该方法利用Scharr 算子能突出弱边缘的优势,结合形态学开闭滤波,从而达到强化弱边缘的效果。 根据形成的弱边缘增强图像,利用最大熵阈值对图像进行分割得到瑕疵。 对光缆生产流水线上采集的图像利用该方法进行测试分析。 实验结果表明,使用改进的弱边缘瑕疵检测算法能更好地检测出弱边缘,从而更加有效地识别表面瑕疵,提高了产品质量。
Abstract:
In the industrial environment,the surface quality of products has become an important part of product quality as well as an important guarantee for the commercial value of commodities. Influenced by factors such as light source,light mode and so on,product surface defects can be prone to form weak edge that the changes in their gray scale are relatively slow. In industrial production,compared with strong edge blemishes,weak edge blemishes are more difficult to be detected due to their gradual change in gray level. Therefore,we propose a method to detect the weak edge defects effectively. In order to strengthen the weak edge,the advantage that Scharr operator canhighlight the weak edge is utilized, combining with the morphological opening and closing filtering, and then the maximum entropythreshold is used to segment the image to get the flaw. So far,the images collected on the production line of optical fiber cable are tested and analyzed. Experiment shows that the improved weak edge detection algorithm can better detect weak edge flaws,which identifiessurface defects more effectively and accordingly improves product quality.

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更新日期/Last Update: 2019-05-10