Title: Directional textures auto-inspection using discrete cosine transform
Authors: Perng, Der-Baau
Chen, Ssu-Han
Department of Industrial Engineering and Management
Keywords: directional texture;discrete cosine transform;defect inspection;machine vision
Issue Date: 2011
Abstract: This paper describes a global image restoration scheme using a discrete cosine transform (DCT) that can be used to detect defects in directional textured surfaces automatically. The input spatial domain image is first transformed into the DCT domain so that the dominant directions of the texture in the input image will be compacted into the orthogonal straight lines or impulses through the direct current (DC) component of the spectrum. The linear primitives associated with the high-energies in the DCT domain are eliminated by reducing them to zero before transforming back to the spatial domain. Finally, the defects, if any, are extracted by the thresholding method. Experiments on a variety of product surfaces with directional textures such as straight, slanted, orthogonal, slanted orthogonal, and oblique linear primitives were conducted in this paper. The proposed scheme would blur directional textures and preserved only local defects if they were initially embedded in the image. Furthermore, some preliminary experiments were also conducted to demonstrate the proposed scheme was insensitive to horizontal and vertical shifting, changes in illumination, and image rotation.
URI: http://hdl.handle.net/11536/15386
ISSN: 0020-7543
DOI: 10.1080/00207543.2010.495087
Volume: 49
Issue: 23
Begin Page: 7171
End Page: 7187
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