NDLI: Fabric defect detection based on fusion technology of multiple algorithm

Content Provider	IEEE Xplore Digital Library
Author	Shengqi Guan
Copyright Year	2010
Description	Author affiliation: College of mechanical & electronic Engineering, Xi'an Polytechnic University, Xi'an, China (Shengqi Guan)
Abstract	As the variety of fabric defects, it is difficult that there has an image processing algorithm suitable for the detection of all defects. A new method was presented for defect detection. Normal texture is filtered by Fourier transform in the frequency domain and it is increased to the serious defect information. Wavelet single decomposition and approximate sub-image filtering are combined to inhibit the normal texture high frequency and low frequency information, and to enhance the contrast of common defect information. The normal texture information and defect information are separated by orthogonal wavelet multi-decomposition for discrete small defect detection. On this basis, the image characteristics are extracted in sub-windows of image; then the defects are identified by neural network. Experimental results show that the method is effectiveness.
File Size	469519
File Format	PDF
ISBN	9781424468928
e-ISBN	9781424468935
DOI	10.1109/ICSPS.2010.5555667
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-05
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multiple algorithm Accuracy Wavelet transform Feature extraction Information filters Fourier transform Fabrics Frequency domain analysis Fusion technolog Defect detection
Content Type	Text
Resource Type	Article

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