Research On Image Information Detection Method Of Fabric Defects

Textile industry is very advanced in our country, the industry is very competitive also, in the industry based on the key is the fabric quality, fabric defects are main factors affecting the quality of cloth, and defect detection is the important guarantee to ensure the quality of cloth. The traditional manual operation, the intensity of labor is big and slow speed detection, the detection accuracy is directly related to labor workers experience and level of fatigue, lack of consistency and reliability. So the modern technology is the fabric defects automatic detection, is con trolling the quality of the piece goods in the production of textile industry trend. Since the 1990 s, the automatic cloth inspection has always been the hot spot of the textile industrial automation research. In this paper, we study a kind of fabric defects automatic detection based on machine vision system design scheme, including the overall design of system software and hardware design of image acquisition module, defect detection algorithm and defect classification algorithm in the research and design, etc. The cloth image acquisition, defect detection algorithm is the key of the system design.These mainly discusses the application of mathematical morphology in fabric defect detection, and use the platform of software to detect including hole, warp-lacking, jump and plasma spot four types of defects, for example, the reliability of the morphological processing algorithm is verified by experiment. By applying the traditional morphological open operation to remove noise processing, so as to highlight the defect information. Finally to the fabric defects for simple area computation, research laid the foundation for subsequent identification work.