Machine Vision Based Detection Method for Surface Crack of Ceramic Tile

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.