Novel Method of FKP Feature Extraction Using Mechanical Variable
Sukhdev Singh1, Chander Kant2
1Sukhdev Singh, Department of Computer Science & Applications, Kurukshetra University, Kurukshetra, India.
2Chander Kant, Department of Computer Science & Applications, Kurukshetra University, Kurukshetra, India.
Manuscript received on 15 August 2019 | Revised Manuscript received on 22 August 2019 | Manuscript published on 30 August 2019 | PP: 3021-3025 | Volume-8 Issue-10, August 2019 | Retrieval Number: J94630881019/19©BEIESP | DOI: 10.35940/ijitee.J9463.0881019
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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: Feature extraction is one of the most essential phase in biometric authentication. It helps in extracting and measuring the biometric image as ideal as possible. These features sets can be used further for image matching, recognition or learning techniques in supervised algorithms. In the proposed work a novel features extraction method for finger knuckle print is explored with comparative analysis. The proposed scheme is based on different mechanical variables and its efficiency also proved by plotting different curves in Matlab R2009a.
Keywords: Finger Knuckle Print, Feature Extraction, Digital Image Processing, Recognition Rate.
Scope of the Article: Image Processing and Pattern Recognition