Research And Application Of Visual Inspection Technology For The Large Area Of Leather Surface

With the development of science and technology and the improvement of standard of living, home sofa, car seat, leather garments, leather shoes and other leather products are used more and more widely, leather products processing quality and efficiency requirements are also getting higher and higher. As a result of leather raw materials from animal fur (leather, sheepskin, pigskin), its surface will inevitably exist various defects, such as spots, wrinkles, scars, holes and other defects, therefore in the raw leather processing, the available efficient area (excluding defective, acquiring available area) must be first detected.Long term since the leather products processing in detection, layout, cutting mainly rely on manual completed, the labor intensity is large, the subjective factors influencing severity, poor consistency, raw leather waste rate high. In order to make effective use of leather raw materials, improve product quality and production efficiency, reduce production costs, leather products processing technology and equipment gradually to the efficient, reliable automated direction, especially the leather surface artificial detection technology has gradually been replaced by machine vision detection.This dissertation combines Zhejiang province key science and technology project" leather products pseudo flexible manufacturing technology development (Grant NO.2003C11023)", for the large area of raw materials for leather (cowhide) surface using computer vision detection method to get the available area, study of leather surface defects detection and the available area extraction theory method, to solve some key technologies, the corresponding development the prototype, and through the experimental research to validate the feasibility of theoretical method and the effectiveness of system. The main contents of this paper include:First, This paper summarizes the current image denoising methods of basic principle and characteristics, In view of the problem of mixed noise influence on image quality in the process of leather image acquisition.In the conditions of do not damage the leather texture detail information, Study on the joint denoising technology of based on wavelet adaptive threshold and median filtering, Accurate retention important leather surface information of leather boundary, lines, spots, wrinkles, scars, depressions, holes and other defects, And through experimental verification of the denoising effect.Second, In view of the problems of small field of view in industrial CCD, leather soft material properties and leather cutting machine structure of restrictions and other issues, from theoretical and practical perspective to study on industrial scene image mosaic of the real-time and reliability, Research the image splicing technology based on the Gabor_Zernike moments of geometric similarity triangle texture block, combined with the hardware conditions, to solve the problems of image mosaicing algorithm complex, slow speed. In order to realize a large area of leather fast and accurate image sequence stitching in visual detection, to obtain the overall characteristics of leather, show large leather global information.Third. In view of the problems of leather texture and defects of global random, feature extraction is difficult and the large amount of calculation. Study on fuzzy clustering based on Particle Swarm Optimization of leather surface defect real-time detection technology, the use of particle swarm fast global optimization, combining fuzzy clustering features, using the maximum distance between and within class minimum distance method for rapid extraction the best feature of defect area and high grade skin area, instead of the traditional fuzzy clustering algorithm based on gradient descent iterative process, enhance the ability of global search and improve the clustering efficiency, realize the defect region and leather quality region rapid clustering, Through image segmentation is processed to derive usable area. Aiming at the problem of real-time leather flaw detection, by each of a detected leather image wavelet decomposition. Extraction of each layer of low frequency sub image energy and local homogeneity feature analysis. Automatically determine the resolution series and select decomposition sub image of wavelet frequency to reconstruct, finally in the reconstructed image by using the adaptive threshold method to divide into the defect area and the quality area, the texture image defect detection is converted into a non-texture image defect detection..Fourth, In order to realize the leather sample intelligent nesting and cutting process, for leather available area boundary and contour vectorization of bitmap processing. In view of the problems of breakpoint, discontinuous and branch lines in the generation of complex irregular leather available area boundary and contour vector graphics, a new contour bitmap vectorization technology of improved chain code representation is presented, realization of vector graphics arbitrary edit for leather available area. To meet the requirements of intelligent nesting, implementation of the leather sample without drawing processing.Fifth, Based on machine vision detection technology to build a large leather raw surface of the vision detection system, Implementation the functions of image acquisition, stitching, defect recognition and the available area extraction, to meet technical requirements of the industrial production.Sixth. The combination of theoretical research. In the numerical control leather cutting machine for test of mixed noise denoising effect, texture block image stitching, defect detection and leather available region contour vectorization of bitmap, validation of the technical feasibility and system working effectiveness.