激光与光电子学进展, 2019, 56 (13): 131006, 网络出版: 2019-07-11
基于机器视觉的聚氯乙烯管材表面缺陷检测 下载: 1253次
Surface Defect Detection of Polyvinyl Chloride Pipes Based on Machine Vision
图 & 表
图 2. PVC管材表面缺陷图。(a)凹坑;(b)气泡;(c)杂质;(d)褶皱;(e)划痕;(f)污染
Fig. 2. Surface defects on PVC pipes. (a) Pits; (b) bubbles; (c) impurities; (d) wrinkles; (e) scratches; (f) pollution
图 4. Gamma变换以及对比图。(a)原图;(b)褶皱区域;(c) Gamma变换效果图
Fig. 4. Gamma transformation and contrast diagrams. (a) Original image; (b) area of wrinkle; (c) image after Gamma transformation
图 7. 快速区域生长示意图。(a)原图矩阵中的生长点;(b)每行生长结果;(c)最终生长结果
Fig. 7. Schematic of fast region growing. (a) Growing point in original matrix; (b) growing results per line; (c) final growing result
图 8. 分块效果图。(a)点状缺陷;(b)分块投影;(c)分块一阶微分
Fig. 8. Effect of block processing. (a) Point defect; (b) block projection; (c) block first-order differential
表 1Gamma变换法的用时对比
Table1. Comparison of time cost for Gamma transformation
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表 2区域生长法的用时对比
Table2. Comparison of time cost for region growing
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李书华, 周亚同, 王丹, 何静飞, 张忠伟. 基于机器视觉的聚氯乙烯管材表面缺陷检测[J]. 激光与光电子学进展, 2019, 56(13): 131006. Shuhua Li, Yatong Zhou, Dan Wang, Jingfei He, Zhongwei Zhang. Surface Defect Detection of Polyvinyl Chloride Pipes Based on Machine Vision[J]. Laser & Optoelectronics Progress, 2019, 56(13): 131006.