Title: Palm pattern recognition using scale invariant feature transform

Authors: M. Kasiselvanathan; V. Sangeetha; A. Kalaiselvi

Addresses: Electronics and Communication Engineering, Sri Ramakrishna Engineering College, Coimbatore, Tamil Nadu, 641 022, India ' Electronics and Communication Engineering, Sri Ramakrishna Engineering College, Coimbatore, Tamil Nadu, 641 022, India ' Electronics and Communication Engineering, Sri Ramakrishna Engineering College, Coimbatore, Tamil Nadu, 641 022, India

Abstract: In this research paper, we propose an efficient scale invariant feature transform (SIFT) for palm pattern recognition. A fingerprint recognition which is efficient for individual authentication based on fingerprint pattern. This method leads to fraudulent because it could be extracted easily from individuals. The SIFT method based on feature detection overcomes the above problem and is a combination of fast key point detector and visual descriptor. Using SIFT method contactless palm pattern images can be acquired, matched, recognised, authenticated and their matching performance are simulated using OpenCV. The experimental results show that SIFT method provides significantly fast and improved performance than the conventional methods like oriented FAST and rotated BRIEF (ORB).

Keywords: image matching; biometrics; palm pattern; feature detection; scale invariant feature transform; SIFT; ORB.

DOI: 10.1504/IJISC.2020.104826

International Journal of Intelligence and Sustainable Computing, 2020 Vol.1 No.1, pp.44 - 52

Received: 16 Aug 2018
Accepted: 13 Nov 2018
Published online: 03 Feb 2020 *