DocumentCode :
2767216
Title :
Palmprint Recognition: Two level Structure Matching
Author :
Pradeep, S.N. ; Jain, Mayur D. ; Prakash, Chandra ; Raman, Balasubramanian
Author_Institution :
Sarnoff Innovative Technol., Bangalore
fYear :
0
fDate :
0-0 0
Firstpage :
664
Lastpage :
669
Abstract :
We introduce palmprint recognition, one of the most reliable personal identification methods in the biometric technology. In this paper, a new approach to the palmprint matching by constructing local and global line feature structures is presented. The datum point of palmprint acts as an important registration due to its remarkable advantage about its spatial location. Initially we define all possible local line feature structures constructed with adjacent lines, around datum point. Through a first level match using these local line feature structures, we get best matched line features. Using these best matched line features, we construct a global line feature structure of palmprint with datum point as reference. This global line feature structure is spread across in four quadrants, datum point being the origin. We then carry out a second level match using this global structure of palmprint to reliably determine its uniqueness. The two levels of matching using local and global line feature structures helps in effective palmprint recognition. With several palmprint images, we tested out proposed verification system and the experimental result shows that the performance of our algorithm is good.
Keywords :
biometrics (access control); image matching; image registration; biometric technology; datum registration; global line feature structures; local line feature structures; palmprint recognition; personal identification; two level structure matching; Authentication; Biometrics; Feature extraction; Fingerprint recognition; Geometry; Humans; Image resolution; Robustness; Stability; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9490-9
Type :
conf
DOI :
10.1109/IJCNN.2006.246747
Filename :
1716158
Link To Document :
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