TY - GEN
T1 - Realizing hand-based biometrics based on visible and infrared imagery
AU - Michael, Goh Kah Ong
AU - Connie, Tee
AU - Chin, Teo Chuan
AU - Foon, Neo Han
AU - Jin, Andrew Teoh Beng
PY - 2010
Y1 - 2010
N2 - This paper describes a hand-based biometric system by using visible and infrared imagery. We develop an acquisition device which could capture both color and infrared hand images. We modify an ordinary web camera to capture the hand vein that normally requires specialized infrared sensor. Our design is simple and low-cost, and we do not need additional installation of special apparatus. The device can capture the epidermal and subcutaneous features from the hand simultaneously. In specific, we acquire four independent, yet complementary features namely palm print, knuckle print, palm vein, and finger vein, from the hand for recognition. As a low-resolution sensor is deployed in this study, the images quality may be slightly poorer than those acquired using high resolution scanner or CCD camera. The line and ridge patterns on the hand may not appear clear. Therefore, we propose a pre-processing technique to enhance the contrast and sharpness of the images so that the dominant print and line features can be highlighted and become disguisable from the background. After that, we use a simple feature extractor called Directional Coding to obtain useful representation of the hand modalities. The hand features are fused using Support Vector Machine (SVM). The fusion of these features yields promising result for practical multi-modal biometrics system.
AB - This paper describes a hand-based biometric system by using visible and infrared imagery. We develop an acquisition device which could capture both color and infrared hand images. We modify an ordinary web camera to capture the hand vein that normally requires specialized infrared sensor. Our design is simple and low-cost, and we do not need additional installation of special apparatus. The device can capture the epidermal and subcutaneous features from the hand simultaneously. In specific, we acquire four independent, yet complementary features namely palm print, knuckle print, palm vein, and finger vein, from the hand for recognition. As a low-resolution sensor is deployed in this study, the images quality may be slightly poorer than those acquired using high resolution scanner or CCD camera. The line and ridge patterns on the hand may not appear clear. Therefore, we propose a pre-processing technique to enhance the contrast and sharpness of the images so that the dominant print and line features can be highlighted and become disguisable from the background. After that, we use a simple feature extractor called Directional Coding to obtain useful representation of the hand modalities. The hand features are fused using Support Vector Machine (SVM). The fusion of these features yields promising result for practical multi-modal biometrics system.
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U2 - 10.1007/978-3-642-17534-3_75
DO - 10.1007/978-3-642-17534-3_75
M3 - Conference contribution
AN - SCOPUS:78650198202
SN - 3642175333
SN - 9783642175336
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 606
EP - 615
BT - Neural Information Processing
T2 - 17th International Conference on Neural Information Processing, ICONIP 2010
Y2 - 22 November 2010 through 25 November 2010
ER -