%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