Fingerprint Detection Technique Using SURF, PHOG & PCA Feature Extraction Process
R.Balamurugan1, S.Mythili2, S. Perumal3
1Mr. R. Balamurugan, Department of Computer Science, School of computing Sciences, VISTAS, Chennai, India.
2Mrs. S. Mythili, Department of Computer Science, School of Computing Sciences, VISTAS, Chennai, India.
3Dr. S. Perumal , Department of Computer Science, School of Computing Sciences, VISTAS, Chennai, India.
Manuscript received on 12 August 2019. | Revised Manuscript received on 16 August 2019. | Manuscript published on 30 September 2019. | PP: 7266-7269 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6341098319/2019©BEIESP | DOI: 10.35940/ijrte.C6341.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The biometric way of identifying a person are wildly spared around many industries and organizations. The identification techniques followed for the biometric are mostly common in using fingerprint detection for individual identification. Basically password based security systems are cracked through many techniques, which makes many problem to the organization using password for security purpose. The spoof fingerprint way of identifying a person is becoming very famous in providing security to the users. The research work focuses on proposing a novel approach in merging fingerprint features all together in one static software approach. The features identified from the fingerprints are extracted using histogram equations in initial step of fingerprint security system. The Gabor wavelet transformation techniques is one of the images processing technique used for identifying features. The features are maintained carefully with applying dynamic score level integration. The efficiency of proposed work is checked with LivDet 2011 dataset. The rate of classification shows 9.625% and error rate is 2.27%.
Keywords: Gabor Filters, Pyramid Histogram of Oriented Gradients (PHOG), Speeded up Robust Features (SURF), Principal Component Analysis (PCA), Texture Analysis, Biometric Security,
Scope of the Article: Computational Techniques in Civil Engineering