IEEE Spectrum
Pyramid edge detection based on stack filter
Pattern Recognition Letters
Biometrics, Personal Identification in Networked Society: Personal Identification in Networked Society
Palmprint recognition using eigenpalms features
Pattern Recognition Letters
Fuzzy Directional Element Energy Feature (FDEEF) Based Palmprint Identification
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Fisherpalms based palmprint recognition
Pattern Recognition Letters
Feature Extraction Method for Palmprint Considering Elimination of Creases
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
A study of identical twins’ palmprints for personal authentication
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Texture-based palmprint retrieval using a layered search scheme for personal identification
IEEE Transactions on Multimedia
Palm recognition using fast sparse coding algorithm
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Palmprint recognition method based on a new kernel sparse representation method
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
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Recently,researchers have been paying an excessive amount of attention to biometric palmprint which has gained popularity and received significant prominence due to its high stability and uniqueness. In this study, two certain filters have been taken into consideration, namely Gabor filter and Circular Gabor filter which are used to obtain feature information from two distinguishing regions of interest, square and inscribed circle areas as the central part sub-images and the two palmprint images are compared with one another in terms of their hamming distance. The outcomes of the experiment gave an indication to the fact that circular Gabor Filter had a comparatively better performance than traditional one in extracting distinct feature information.