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%.