Version 1
: Received: 25 January 2018 / Approved: 26 January 2018 / Online: 26 January 2018 (06:35:56 CET)
How to cite:
Zhuang, L.; Guan, Y. Improvement of Illumination-Insensitive Feathers for Face Recognition under Complex Illumination Conditions. Preprints2018, 2018010250. https://doi.org/10.20944/preprints201801.0250.v1
Zhuang, L.; Guan, Y. Improvement of Illumination-Insensitive Feathers for Face Recognition under Complex Illumination Conditions. Preprints 2018, 2018010250. https://doi.org/10.20944/preprints201801.0250.v1
Zhuang, L.; Guan, Y. Improvement of Illumination-Insensitive Feathers for Face Recognition under Complex Illumination Conditions. Preprints2018, 2018010250. https://doi.org/10.20944/preprints201801.0250.v1
APA Style
Zhuang, L., & Guan, Y. (2018). Improvement of Illumination-Insensitive Feathers for Face Recognition under Complex Illumination Conditions. Preprints. https://doi.org/10.20944/preprints201801.0250.v1
Chicago/Turabian Style
Zhuang, L. and Yepeng Guan. 2018 "Improvement of Illumination-Insensitive Feathers for Face Recognition under Complex Illumination Conditions" Preprints. https://doi.org/10.20944/preprints201801.0250.v1
Abstract
Complex illumination condition is one of the most critical challenging problems for practical face recognition. In this paper, we propose a novel method to improve the illumination invariants for solving this challenge. Firstly, a new method based on the Lambert reflectance model is proposed to extract illumination invariant, which is less insensitive to complex illumination variations. Secondly, in order to repair the defects caused by process of illumination invariants extraction, Fast Mean Filter is utilized to smooth and remove noise. Lastly, for raising the richness of information in output image, a nonlinear normalization transformation is proposed. Compared with the state-of-the-arts, experimental results show that the proposed method can extract more robust illumination invariants. Apart from it, the richness of information in processed image is greater and superior performance in face recognition rate is superior.
Keywords
improvement; illumination invariants; face recognition; complex illumination
Subject
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
