| 郑叶欣,王耀南,周显恩,蒋笑笑,彭玉,刘远强.基于POBT的空瓶规则纹路区域缺陷检测[J].电子测量与仪器学报,2017,31(4):549-558 |
| 基于POBT的空瓶规则纹路区域缺陷检测 |
| Empty bottle texture area defect detection based on POBT |
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| DOI：10.13382/j.jemi.2017.04.009 |
| 中文关键词: 机器视觉 玻璃瓶 纹路缺陷检测 仅基于相位变换的检测 自适应阈值分割 |
| 英文关键词:machine vision glass bottle texture area defect detection POBT adaptive thresholding |
| 基金项目:国家自然科学基金（61573134）、佛山市创新科研团队（00165331140527103）资助项目 |
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| Author | Institution |
| Zheng Yexin | National Engineering Laboratory for Robot Visual Perception and Control Technology, College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; |
| Wang Yaonan | National Engineering Laboratory for Robot Visual Perception and Control Technology, College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; |
| Zhou Xian′en | National Engineering Laboratory for Robot Visual Perception and Control Technology, College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; |
| Jiang Xiaoxiao | National Engineering Laboratory for Robot Visual Perception and Control Technology, College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; |
| Peng Yu | National Engineering Laboratory for Robot Visual Perception and Control Technology, College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; |
| Liu Yuanqiang | Foshan Xiangde Intelligent Technology Co.Ltd.,Foshan 528000,China |
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| 中文摘要: |
| 现有的玻璃瓶瓶身质量检测方法中，缺乏对有纹理图案的玻璃瓶的缺陷检测，针对这一问题，提出一了种仅基于相位变换（phase only based transition，POBT）的玻璃瓶纹理区域缺陷检测算法。该算法采用基于灰度投影的方法求取玻璃瓶瓶身中心坐标，利用基于相位的变换方法，通过归一化过程去除玻璃瓶规则纹路区域的低频纹路分量，仅保留下缺陷图像，应用概率修正自适应阈值分割方法对经过POBT变换后去除纹理留下的缺陷的图像进行分割，提取缺陷，并将该分割方法与3种传统型的方法进行对比。实验结果表明，该方法可实现瓶身规则纹路区域的高速高精度缺陷检测。 |
| 英文摘要: |
| To solve the problem that the existing glass bottle detection algorithm only aimed at the smooth surface with no pattern, a glass bottle texture area detection algorithm based on the POBT (phase only based transition) is proposed in the paper. The method first calculates the glass bottle center axis according to the bottle body gray projection, then obtains defect image by removing all the patterns through POBT, which including the process of nomalization in frequency domain to eliminate low frequency component of the glass texture area. At last, it extracts defects by using adaptive probability refined thresholding segmentation on the POBT image and compares the segmentation method with three conventional methods. The experiment result shows that aimed to the glass bottle glass texture area, the method can achieve high precision detection with rapid speed of the glass bottle texture area. |
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