Automatic Classification of Woven Fabric Structure Based on Computer Vision Techniques (Journal of Fiber Bioengineering and Informatics, 2015)
Traditionally woven fabric structure classification is based on manual work in textile industry. This paper\rproposes an automatic approach to classify the three woven fabrics: plain, twill and satin weave. Firstly\r2-D wavelet transform is used to obtain low frequency sub-image in order to reduce the analysis of fabric\rimages. Then graylevel co-occurrence matrix (GLCM) and Gabor wavelet are adopted to extract the\rtexture features of pre-processing fabric images. Finally Probabilistic Neural Network (PNN) is applied\rto classify the three basic woven fabrics. The experimental results demonstrate that the proposed method\rcan automatically, efficiently classify woven fabrics and obtain accurate classification results (93.33%).
Keywords: Woven Fabric Structure; Automatic Classification; 2-D Wavelet Transform; GLCM; Gabor Wavelet; PNN