Performance of detecting defects in textile fabric using Gabor Wavelet with statistical and Morphological filters

Authors:
S. Anitha;V. Radha
Affiliations:
Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, TamilNadu, India;Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, TamilNadu, India
Venue:
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
Year:
2012

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Abstract

Automatic visual inspection is the backbone of any manufacturing industry. Manual inspections of textile fabrics are ineffective due to the fatigue and speed requirement. The Gabor wavelets network provides an effective way to analyze the input images and to extract the fabric features. This paper addresses the functionality of Gabor Wavelet with statistical features and Morphological filtering. The first method extracts statistical features of the input image using Gabor wavelet. Another method combines Gabor wavelet with morphological filtering to select appropriate structuring element. Finally, thresholding of the features are done to produce a binary image. In addition, the performance of the algorithms is evaluated to verify their efficiency in identifying the defective fabric image based on the segmented results.