Palmprint Recognition Using Directional Line Energy Feature

Authors:
Xiangqian Wu;Kuanquan Wang;David Zhang
Affiliations:
Harbin Institute of Technology (HIT), China;Harbin Institute of Technology (HIT), China;Hong Kong Polytechnic University, Kowloon
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Year:
2004

Citing 0
Cited 6

A hierarchical identification method based on improved hand geometry and regional content feature for low-resolution hand images

Signal Processing
A survey of palmprint recognition

Pattern Recognition
Accurate Palmprint Recognition Using Spatial Bags of Local Layered Descriptors

ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Palmprint Recognition Based on Regional Rank Correlation of Directional Features

ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Automated flexion crease identification using internal image seams

Pattern Recognition
A Comparative Study of Palmprint Recognition Algorithms

ACM Computing Surveys (CSUR)

Quantified Score

Hi-index	0.00

Visualization

Abstract

Palm-lines, including the principal lines and wrinkles, can describe a palmprint clearly. This paper presents a novel approach of line feature extraction for palmprint recognition called the directional line energy feature (DLEF). The directional lines in different directions are first extracted using a set of directional line detectors. Then each directional line magnitude image is divided into several overlapped small grids and the magnitudes of the line points in these grids are used to compute the DLEF. A template-matching method based on Euclidean distance is adopted to measure the similarity of two DLEFs. Best results have been obtained when DLEFs with 6 different directions were employed. Accuracies of 97.92% and 97.5% are obtained by using the proposed approach in one-against-one matching and one-against-320 matching, respectively.