Research on lace defect detection based on fingerprint identification method of detail feature points extraction and matching

The development of lace has a profound impact on the economic development and new employment in some regions, so the demand for lace is increasing year by year. However, the quality inspection problem has been troubling the whole lace industry. In order to solve this problem, this paper uses the fingerprint identification method to extract and match the details of feature points to detect the defects of lace images. Firstly, a series of preprocessing is carried out between the template and the image to be matched, including normalization, distinguishing the initial foreground and background color, removing the void and burr, image refinement, etc. Secondly, two kinds of detail feature points, namely, endpoints and bifurcation points, are extracted from the thinning graph and the feature information of lace detail points is counted. Then, three kinds of pseudo feature points, short line, outlier and ring, are removed according to the process of distance and ring method. Finally, the Euclidean distance is used to calculate the distance between each step length of the same feature point in the two images and the current feature point, and the distance is saved. If the coordinates of the pixel points stored within the synchronous length are basically the same, it means that the two images are the same. The experiments show that the proposed algorithm is superior to the compared algorithms in terms of both recognition rate and algorithm speed, which meets the requirements of small and medium-sized lace enterprises.