锻压技术

基于双阈值图像区域生长法的冲压件划痕检测

英文标题：Scratch detection on stamping part based on double threshold image region growth method

作者：田洪志王东兴林建钢陈麒麟

单位：烟台大学

分类号：TP391

出版年,卷(期):页码：2020,45(6):175-181

摘要：

当冲压件划痕缺陷区域的灰度值与背景的灰度值差异不大时，使用传统的图像分割方法易出现噪声较多或划痕特征无法提取的情况。为此，提出了一种基于动态阈值分割的双阈值图像区域生长法。首先，对采集的冲压件图像进行两次不同阈值的动态阈值分割，得到两个不同阈值的二值图像；其次，结合两个不同阈值的二值图像使用区域生长法得到优化二值图像；最后，对生长完成后的优化二值图像通过面积和结构因子特征参数进行区域筛选，提取划痕缺陷。实验结果表明，使用本方法检测冲压件划痕缺陷，能够满足工厂检测要求，具有检测效率高、准确性高的优点。

When the gray value of scratched defect area for stamping part has little difference with that of background, the traditional image segmentation method is prone to producing too much noise or the situation that the scratch features cannot be extracted. Therefore, the double threshold image region growth method based on dynamic threshold segmentation was proposed. Firstly, the collected images of stamping part were segmented by dynamic threshold with two different thresholds, and binary images with two different thresholds were obtained. Then, the optimized binary images were dstained by region growth method combining binary images with two different thresholds. Finally, the optimized binary image after the growth was screened by area and structure factor characteristic parameters to extract the scratch defects. The experimental results show that using this method to detect the scratch defects of stamping parts meets the requirements of factory inspection and has the advantages of high detection efficiency and high accuracy.

基金项目：

国家自然科学基金青年项目(11604285)

田洪志(1994-)，男，硕士研究生 E-mail：1017694473@qq.com 通讯作者：王东兴(1964-)，男，博士，教授 E-mail：dxwang@ytu.edu.cn

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