陶瓷瓦表面缺陷的自动检测是该产业升级中亟待解决的问题。陶瓷瓦表面为立体的形态结构且存在大量的花纹,这将导致陶瓷瓦表面光照不均匀,会对缺陷自动检测造成许多干扰。为此,本文提出基于多尺度Hessian矩阵滤波的陶瓷瓦表面裂纹检测算法。首先使用带通滤波抑制陶瓷瓦图像背景及噪声并突出陶瓷瓦裂纹特征;然后,利用多尺度Hessian矩阵的特征值构建陶瓷瓦裂纹相似性函数,实现陶瓷瓦裂纹特征增强;最后,采用二值化和形态学处理的方式,提取裂纹的参数信息。通过实验表明,该算法可以有效去除复杂背景的干扰,提取出完整的陶瓷瓦表面裂纹,且运算效率较高,准确率高达95%。

Automatic detection of ceramic tilt surface defects is an urgent problem in the upgrading of the industry. The surface of the ceramic tile has a three-dimensional morphological structure and there are a lot of patterns, which will result in uneven illumination on the surface of the ceramic tile and cause many interferences to automatic defect detection. Therefore, this paper proposes a surface crack detection method for the ceramic tile based on multi-scale Hessian matrix filtering. First, band-pass filtering is used to suppress the background and noise of ceramic tile image and highlight the crack characteristics of the ceramic tile. Then, using the eigenvalues of the Hessian matrix, the crack similarity function of ceramic tile is constructed to enhance the crack characteristics of ceramic tile. Finally, the binarization and morphological processing methods are used to extract the crack parameter information. Experimental results show that the algorithm can effectively remove the interference from complex background, extract the complete surface cracks of the ceramic tile, and has high calculation efficiency with an accuracy rate as high as 95%.