Periodic Pattern Surface Defects Detection Using Gabor Filter
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 5
Abstract
surface defects detection is an important aspect of quality control. The surface defects inspection is required on finished products like, leather, textiles, steel rolls etc in order to grade the product and value them. Till recently, these quality inspections are carried out manually by experienced people. The processing of colored images with the pair of features results in better defect analysis than the traditional gray level defect detection techniques. In this paper, for periodic patterns, we present a gabor filtering techniques that is employed to detect the defects on the gray level texture images by considering pair of features. In this, energy is obtained by convolving gabor filter with respective images. The results obtained with this method show 80% - 90% success rate in detecting the defects with different texture.
Authors and Affiliations
P. Bala Prasanthi, M. Sirisha, Shaik Asma
Keywords
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