Fusion of Visible and Infrared Image Features for Face Recognition
R.Sumalatha1, S.Sujana2, R.Varaprasada Rao3
1Dr. R. Sumalathairst, Department of ECE, Vardhaman College of Engineering, Hyderabad (Telangana), India.
2S.Sujana, Department of ECE, Vardhaman College of Engineering, Hyderabad (Telangana), India.
3R. Varaprasada Rao, Department of ECE, RGMCET, Kurnool (Andhra Pradesh), India.
Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 1-4 | Volume-8 Issue-5, June 2019 | Retrieval Number: D6395048419/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: In this paper we used Local Binary Pattern (LBP), Features from accelerated segment test (FAST), Scale Invariant Features Transformations (SIFT), Speed Up Robust Feature Transformations (SURF), Binary Robust Invariant Scalable Key points (BRISK), Maximally Stable Extremal Regions (MSER) feature extraction methods to evaluate the performance of face recognition system with fusion of visible and infrared images. These six feature extraction methods are tested and analyzed on OTCBVS database under various illumination and expressions of multiple persons. The results shows that FAST, SIFT and SURF provides high precision rate and recall rate than other methods.
Keywords: Thermal Face Recognition, Feature Extraction, Fusion, LBP, SIFT, FAST, SURF
Scope of the Article: Thermal Engineering