激光与光电子学进展, 2020, 57 (8): 081004, 网络出版: 2020-04-03
基于机器视觉的陶瓷瓦表面裂纹检测方法 下载: 1376次
Machine Vision Based Detection Method for Surface Crack of Ceramic Tile
陶瓷瓦 机器视觉 裂纹检测 主成分分析 二值化 ceramic tile machine vision crack detection principal component analysis binarization
摘要
针对具有复杂背景的陶瓷瓦表面裂纹检测困难的问题,提出了一种基于主成分分析的陶瓷瓦表面裂纹检测算法。首先,将陶瓷瓦彩色图像转换为红色通道图像进行预处理;然后,采用主成分分析的方法重构陶瓷瓦图像,将预处理图像与重构图像进行差分处理,得到具有裂纹信息的图像;最后,采用二值化和形态学处理,提取裂纹的参数信息。实验表明,该算法可以检测出具有立体形态结构和复杂背景干扰的陶瓷瓦裂纹,相比其他算法检测速度快,准确率高达96%。
Abstract
In view of the difficulty in detecting the surface cracks of ceramic tile with complex background, this paper presents an algorithm for detecting the surface cracks of ceramic tile based on principal component analysis. First, red channel image converted from the ceramic tile color image was preprocessed. Then, the principal component analysis method was used to reconstruct the image of ceramic tile. The image with crack information was obtained by differential processing between the preprocessed image and the reconstructed image. Finally, binary and morphological processing methods were used to extract the parameter information of cracks. Experiments show that the algorithm can detect the cracks of ceramic tile with three-dimensional morphological structure and complex background interference, faster detection speed with accuracy rate as high as 96% can be achieved compared with other algorithms.
李强, 曾曙光, 郑胜, 肖焱山, 张绍伟, 李小磊. 基于机器视觉的陶瓷瓦表面裂纹检测方法[J]. 激光与光电子学进展, 2020, 57(8): 081004. Qiang Li, Shuguang Zeng, Sheng Zheng, Yanshan Xiao, Shaowei Zhang, Xiaolei Li. Machine Vision Based Detection Method for Surface Crack of Ceramic Tile[J]. Laser & Optoelectronics Progress, 2020, 57(8): 081004.