Title :
Multispectral palmprint recognition using steerable filter
Author :
Tamrakar, Deepti ; Khanna, Pritee
Author_Institution :
Design & Manuf., PDPM Indian Inst. of Inf. Technol., Jabalpur, India
Abstract :
This paper presents a multispectral palmprint recognition approach based on palm line orientation feature extracted with high order steerable filter. Gaussian function is used as isotropic window to design a high order steerable filter. The orientation features are selected as per dominant filter response for a particular orientation. Optimum values for parameters, i.e., standard deviation and number of orientations are found experimentally in order to obtain low equal error rate (EER) and high correct identification rate (CIR). Weighted score level fusion strategy is applied to combine the score of all spectral palmprints. A recognition rate of 99.97% is achieved with high decidability index (DI) and low EER. Further, the proposed approach is compared with traditional competitive code method for multispectral PolyU palmprint database.
Keywords :
Gaussian processes; feature extraction; image filtering; image fusion; palmprint recognition; spectral analysis; CIR; DI; EER; Gaussian function; correct identification rate; decidability index; equal-error rate; high-order steerable filter; isotropic window; multispectral PolyU palmprint database; multispectral palmprint recognition approach; optimum parameter values; orientation feature selection; orientation number; palm line orientation feature extraction; recognition rate; spectral palmprints; standard deviation; weighted score level fusion strategy; Accuracy; Approximation methods; Databases; Feature extraction; Image recognition; Pattern recognition; Standards; Multispectral palmprint; Score level fusion; Steerable filter;
Conference_Titel :
Industrial and Information Systems (ICIIS), 2014 9th International Conference on
Conference_Location :
Gwalior
Print_ISBN :
978-1-4799-6499-4
DOI :
10.1109/ICIINFS.2014.7036568
