Texture surface inspection: An artificial immune approach

Abstract

This paper presents a novel approach for visual inspection of textures. The approach applies the artificial immune theory to learning the filters for texture flaw detection, which are invariant to changes of texture orientations and scales. In this paper, defect textures and defect-free textures are regarded as non-self and self respectively, and texture filters are regarded as antibodies. The clonal selection based algorithm is presented to evolve antibodies. Experimental results on TILDA textile images were done to show the feasibility of the proposed method. © Springer-Verlag Berlin Heidelberg 2005.