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 |