张军,张海云,赵玉刚,司马中文.基于机器视觉的瓷砖裂纹检测[J].包装工程,2018,39(9):146-150.
ZHANG Jun,ZHANG Hai-yun,ZHAO Yu-gang,SIMA Zhong-wen.Crack Detection of Ceramic Tiles Based on Machine Vision[J].Packaging Engineering,2018,39(9):146-150. |
| 基于机器视觉的瓷砖裂纹检测 |
| Crack Detection of Ceramic Tiles Based on Machine Vision |
| 投稿时间：2017-12-08 修订日期：2018-05-10 |
| DOI：10.19554/j.cnki.1001-3563.2018.09.026 |
| 中文关键词: 瓷砖 机器视觉 包装线 检测 轮廓提取 |
| 英文关键词: ceramic tile machine vision packaging line detection contour extraction |
| 基金项目:山东省重点研发计划项目（2016GGX103001） |
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| 中文摘要: |
| 目的 线上包装时准确地对带有花纹且背景灰度和裂纹灰度相近的瓷砖表面缺陷进行检测。方法 设计合理的检测机构，选择合适的软硬件，设计各模块的组成；针对裂纹的轮廓难以通过各种算子提取的问题，在自适应形态学预处理后，通过小波变换与形态学融合的差影法提取裂纹边缘、花纹及部分背景信息，筛除掉难以处理的花纹与背景区域。结果 成功得到了缺陷轮廓及对应参数，经对比漏检率为0.02，过检率为0.05。结论 该系统准确率较高，能够满足要求。 |
| 英文摘要: |
| The work aims to detect the surface defects of ceramic tiles with patterns and similar background gray and crack gray during online packaging. A reasonable detection mechanism was designed, suitable software and hardware were selected and compositions of each module were designed. With respect to the problem that it was hard to extract the crack contour through various kinds of operators, after the preprocessing of adaptive morphology, the crack edges, patterns and some background information were extracted in the difference image method through the fusion of wavelet transform and morphology, and then the patterns and background areas hard to process were eliminated. The defect profile and corresponding parameters were successfully obtained. Through comparison, the misdetection rate was 0.02 and the detection rate was 0.05. The system has a higher accuracy and can meet needs. |
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