Fingerprinting of deformed paper images acquired by scanners

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Khaleefah S.H.
Nasrudin M.F.
Mostafa S.A.
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Institute of Electrical and Electronics Engineers Inc.
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Images texture extraction is a core step in image pattern recognition applications such as paper texture identification or fingerprinting. Different methods are applied for paper images texture extraction. Subsequently, one of the well-known methods in images texture extraction is the Locale Binary Pattern (LBP) method. However, the LBP method show a number of drawbacks in paper images texture extraction and two of which are neglecting some texture information of the images and incompetent to some images deformation due to its local view. In this paper, combinations of Gabor filters and a LBP operator are proposed to reduce the effects of the mentioned drawbacks in papers fingerprinting domain. We use self-collected textures from 102 paper images in the test. Consequently, the testing results of the proposed combinations improve paper images identification rate by 28.45% when the Gabor filters have a scale of 9 and an orientation of ?/2 degree. This paper finds that applying Gabor filters prior to LBP method improve the LBP description and the papers fingerprinting accuracy. � 2015 IEEE.
Binary images; Bins; Extraction; Gabor filters; Image processing; Palmprint recognition; Pattern recognition; Binary patterns; Chi-square; Identification rates; Image pattern recognition; Local binary patterns; Paper texture; Texture extraction; Texture information; Image texture