Title: A NOVEL METHOD FOR SHOEPRINTS RECOGNITION AND CLASSIFICATION
Authors: Jing, Min-Quan
Ho, Wei-Jong
Chen, Ling-Hwei
資訊科學與工程研究所
Institute of Computer Science and Engineering
Keywords: Forensic science;Shoeprint;Fourier transforms;Co-occurrence matrix;Principal component transform
Issue Date: 2009
Abstract: In this paper, we present a method for automatically classifying/recognizing the shoeprint images based on the outsole pattern. Shoeprints are distinctive patterns often found at crime scenes that can provide valuable forensic evidence. Directionality is the most obvious feature in these shoeprints. For extracting features corresponding to the directionality, co-occurrence matrices, Fourier transform, and a directional matrix are applied to the shoeprint image. With the stage of principal component transform, the method is invariant to rotation and translation variance. Experimental results demonstrate the performance of the method.
URI: http://hdl.handle.net/11536/14278
ISBN: 978-1-4244-4705-3
Journal: PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-6
Begin Page: 2846
End Page: 2851
Appears in Collections:Conferences Paper