%0 Journal Article %A K. L. Mak and P. Peng %D 2008 %J International Journal of Materials and Textile Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 13, 2008 %T Detecting Defects in Textile Fabrics with Optimal Gabor Filters %U https://publications.waset.org/pdf/12833 %V 13 %X This paper investigates the problem of automated defect detection for textile fabrics and proposes a new optimal filter design method to solve this problem. Gabor Wavelet Network (GWN) is chosen as the major technique to extract the texture features from textile fabrics. Based on the features extracted, an optimal Gabor filter can be designed. In view of this optimal filter, a new semi-supervised defect detection scheme is proposed, which consists of one real-valued Gabor filter and one smoothing filter. The performance of the scheme is evaluated by using an offline test database with 78 homogeneous textile images. The test results exhibit accurate defect detection with low false alarm, thus showing the effectiveness and robustness of the proposed scheme. To evaluate the detection scheme comprehensively, a prototyped detection system is developed to conduct a real time test. The experiment results obtained confirm the efficiency and effectiveness of the proposed detection scheme. %P 116 - 121