Title :
Palmprint matching using pairwise relative angle based Hausdorff distance
Author :
Li, Fang ; Leung, Maylor K H
Author_Institution :
Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
Abstract :
In this paper, we propose a novel approach for palmprint matching. We retrieve line-patterns in a rotation and translation invariant manner that tackles broken line problem. The local structure of line pattern is extracted as a set of pairwise angle relationships, which are simple, invariant to translation and rotation, robust to end-point erosion and segment error, and sufficient for discrimination. The matching experiment has shown encouraging results which implicate that line segments can provide sufficient information for palmprint recognition.
Keywords :
biometrics (access control); image matching; Hausdorff distance; end-point erosion; line-pattern retrieval; pairwise relative angle; palmprint matching; palmprint recognition; segment error; Authentication; Biometrics; Computer errors; Consumer electronics; Data mining; Flowcharts; Histograms; Partitioning algorithms; Robustness; Shape; Hausdorff Distance; biometrics; pairwise relative angle; palmprint;
Conference_Titel :
Consumer Electronics, 2009. ISCE '09. IEEE 13th International Symposium on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4244-2975-2
Electronic_ISBN :
978-1-4244-2976-9
DOI :
10.1109/ISCE.2009.5156869