Title :
Palmprint Matching using Pairwise Relative Angle Histogram
Author :
Li, Fang ; Leung, Maylor K H ; Sim, Larree T g
Author_Institution :
Nanyang Technol. Univ., Singapore
Abstract :
In this paper, we propose a novel approach to retrieve line-patterns from large databases in a rotation and translation invariant manner, at the same time, tackle broken line problem. Line segments are extracted from an image as primitives. Each local structure is represented by a set of pair-wise angle relationships, which are simple, invariant to translation and rotation, robust to end-point erosion, segment error, and sufficient for discrimination. Experiment showed encouraging results which also implicate that line segments could provide sufficient information for palmprint recognition.
Keywords :
feature extraction; fingerprint identification; image matching; image segmentation; broken line problem; end-point erosion; image line segment extraction; large databases; line-pattern retrieval; pairwise angle relationships; pairwise relative angle histogram; palmprint matching; palmprint recognition; Authentication; Biometrics; Cybernetics; Data engineering; Feature extraction; Histograms; Image segmentation; Information retrieval; Machine learning; Shape; Hausdorff distance; Histogram; Line feature; Palmprint; Relative angle;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370131