| 一种微小表面缺陷的机器视觉检测方法 |
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| 引用本文： | 何志勇,孙立宁,芮延年. 一种微小表面缺陷的机器视觉检测方法[J]. 应用科学学报, 2012, 30(5): 531-537. DOI: 10.3969/j.issn.0255-8297.2012.05.015 |
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| 作者姓名： | 何志勇 孙立宁 芮延年 |
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| 作者单位： | 1. 苏州大学机电工程学院，江苏苏州2150212. 苏州大学机器人与微系统研究中心，江苏苏州215021 |
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| 基金项目： | 国家科技重大专项基金，江苏省高校自然科学基金，苏州市科技支撑计划基金 |
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| 摘 要： | 针对表面缺陷在线自动检测应用的特点，提出一种快速检测微小表面缺陷的新方法. 文中分析了Otsu 法分割表面梯度图像中微小缺陷的性能，结合分析结果提出利用梯度图像方差分布搜寻表面缺陷区域的算法，在有表面缺陷的局部区域应用Otsu 法分割图像. 算法性能分析和实验结果表明，该方法可从背景变化不剧烈的表面图像中快速自动检测微小表面缺陷.
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| 关 键 词： | 微小表面缺陷 机器视觉 Otsu 准则 图像分割 |
| 收稿时间： | 2011-11-09 |
| 修稿时间： | 2012-02-20 |
Detection of Small Surface Defects Based on Machine Vision |
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| HE Zhi-yong , SUN Li-ning , RUI Yan-nian. Detection of Small Surface Defects Based on Machine Vision[J]. Journal of Applied Sciences, 2012, 30(5): 531-537. DOI: 10.3969/j.issn.0255-8297.2012.05.015 |
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| Authors: | HE Zhi-yong SUN Li-ning RUI Yan-nian |
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| Affiliation: | 1. School of Mechanical and Electrical Engineering, Soochow University, Suzhou 215021,Jiangsu Province, China;2. Center of Robotics and Microsystem, Soochow University, Suzhou 215021, Jiangsu Province, China |
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| Abstract: | This paper proposes an effective method to be used in fast detection of small surface defects. The space domain gradient method is useful to enhance the surface image. However, we show that the Otsu method cannot produce satisfied result in segmenting small defects in a large surface image. To detect small defects and improve the performance of Otsu method, an algorithm based on the distribution of variances of image blocks is developed to search of small defect regions. Analysis and experiments show that the proposed method can be applied for fast detection of small surface defects. |
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| Keywords: | small surface defects machine vision Otsu criterion image segmentation |
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