Stitching defect detection and classification using wavelet transform and BP neural network

The Fuzzy u-Chart for Sustainable Manufacturing in the Vietnam Textile Dyeing Industry

“…As customers nowadays have a stronger negotiating power, providing them better quality products/services with a reasonable price becomes ever so critical to the survival and development of every business organization [41,42]. Lee et al [43] indicated that a failure in achieving customers' expected quality will lead to a long production cycle time, an increase in production and warranty cost, as well as a significant defection in the number of customers.…”

“…Literally, Wong et al [41] provided a critical review of several approaches in detecting different defects and found that their focus was mainly on defect detection instead of defect diagnosis to identify root causes of defects and implement corrective actions. Lee et al [43] further pinpointed that the existing detection methods treat defects individually without considering their relationships.…”

“…The importance of workmanship is derived from major parts of the processes being handled by workers practical working experience, which directly influences the quality of the products manufactured. In such industries, the quality of final products practically depends on the subjective perception, knowledge, mood and behavior of the inspectors, also known as quality controllers or assurers who check individual parts, semi-products and final products at different stages in the processes to make sure that their products meet certain specifications set by customers [41]. Consequently, with the manual inspection of random samples, certain limitations in terms of inaccuracy, inconsistency and inefficiency, are obviously inevitable; hence, the recorded data are considered fuzzy [4,41,44].…”

Application of Wavelet Transform Method for Textile Material Feature Extraction

“…As computer technology develops, rapid image processing and pattern recognition can be performed quickly and inexpensively. It therefore becomes increasingly popular for computer aided feature extraction, defect detection, quality classification and decision making (Deng et al, 2011;Han & Shi, 2007;Liu et al, 2011a;Liu et al, 2011b;Mak & Peng, 2008;Mak et al, 2009;Wong et al, 2009;Zhang et al, 2010b) in the textile field. Thus, it is the trend that automated image-based inspection replaces human inspection, and improved feature extraction methods will accelerate the process.…”

“…Texture analysis has played an important role in the automatic visual inspection of textile surfaces. Among many methods, the wavelet transform tool has been studied for analysing images and extracting important information for improved pattern recognition (Deng et al, 2011;Han & Shi, 2007;Liu et al, 2011a;Ngan et al, 2005;Wong et al, 2009;Zhang et al, 2007Zhang et al, , 2010b.…”