Abstract
Quality control is one of the basic issues in textile industry. Analysis of texture content in digital images plays an important role in the automated visual inspection of textile images to detect their defects. In this paper, a system for automated visual inspection of textiles is discussed. A detailed system configuration is presented and a fault detection algorithm is proposed. Industrial vision systems must operate in real-time, produce a low false alarm rate and be flexible to accommodate variations in inspection sites. This was the rationale behind developing a detection algorithm which employs simple statistical features (mean, variance, median). The intent was to utilize such features to make the calculations simple and fast for the system to be suitable for real-time applications. The performance of the system was evaluated on plain fabrics with different types of textile flaws. The results indicate that the system can detect flaws which vary drastically in physical dimension and nature with a very low false detection rate.
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