12/17/2022 0 Comments Textile vision software![]() ![]() The proposed method uses a statistical based approach for the inspection and detection of the defect on woven/knitted fabric collected from the textile industry. ![]() The purpose of this paper is to automate the detection and classification of texture defects by computerize software. The price of the fabric is reduced to 45%-65% due to presence of various defects. Visual inspection system consumes a lot of time and are error prone. Due to increasing demand for quality fabrics it is thus important to produce the defect free high quality fabric. ![]() Textile industry is one of the largest and oldest sectors in the India and has a formidable presence in national economy in terms of output, investment and employment. This paper presents a detailed description of a fast algorithm for defect detection in textile surfaces and an evaluation of the experimental results for 137 digitized images of representative defects in woven fabrics collected from a larger sample provided by textile companies. Unfortunately, despite the fact that they achieve good results, they are computationally complex and therefore not suitable for real-time applications, since as the complexity of an algorithm grows, it becomes more and more difficult to execute the image examination in real time. Many texture segmentation techniques have been presented in the literature. It is important that the software core of such a system is based on a robust, fast texture segmentation technique. To increase accuracy, attempts are made to enhance traditional human inspection by automated visual systems, which employ cameras and image processing routines. There is a strong interest in expert systems to assist in complex defect identification procedures. ![]()
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