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Enhanced Fingernail Recognition based on GLCM, SIFT and NN
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 180 - Number 26 |
| Year of Publication: 2018 |
| Authors: Silky, Sonika Jindal |
10.5120/ijca2018916597
|
Silky, Sonika Jindal . Enhanced Fingernail Recognition based on GLCM, SIFT and NN. International Journal of Computer Applications. 180, 26 ( Mar 2018), 18-22. DOI=10.5120/ijca2018916597
Abstract
Biometric validation innovations, for example, unique mark, face, iris, and vein, have been across the board in numerous applications from singular convenient gadgets to national ID administration frameworks. Besides, moderately more up to date biometric validation modalities including eye development, lip-movement, and so on, have been additionally looked into and created keeping in mind the end goal to enhance confirmation exactness and an ease of use of a biometric verification framework. What's more, some these sorts of modalities are powerful as a liveness identification strategy, which cannot just enhance verification exactness in customary biometric confirmation frameworks, yet additionally diminish dangers with respect to hostile to mocking assaults. This paper propose a GSN (GLCM, SIFT, NN) based finger nail recognition technique. GLCM is used for feature extraction; SIFT for Key-point extraction and NN for recognition.
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