Newborn footprint recognition using subspace learning methods

Authors:
Wei Jia;Jie Gui;Rong-Xiang Hu;Ying-Ke Lei;Xue-Yang Xiao
Affiliations:
Hefei Institute of Intelligent Machines, CAS, Hefei, China;Hefei Institute of Intelligent Machines, CAS, Hefei, China and Department of Automation, University of Science and Technology of China;Hefei Institute of Intelligent Machines, CAS, Hefei, China and Department of Automation, University of Science and Technology of China;Hefei Institute of Intelligent Machines, CAS, Hefei, China and Department of Automation, University of Science and Technology of China and Department of Information, Electronic Engineering Institu ...;Hefei Institute of Intelligent Machines, CAS, Hefei, China and Department of Automation, University of Science and Technology of China
Venue:
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Year:
2010

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Abstract

In this paper, we propose a novel online newborn personal authentication system based on footprint recognition. Compared with traditional offline footprinting scheme, the proposed system can capture digital footprint images with high quality. We also develop a preprocessing method for orientation and scale normalization. In this way, a coordinate system is defined to align the images and a region of interest (ROI) is cropped. In recognition stage, several representative subspace learning methods such as PCA, LDA are exploited for recognition. A newborn footprint database is established to examine the performance of the proposed system, and the promising experimental results demonstrate the effectiveness of proposed system.