Face Recognition Algorithm Based on Fast Computation of Orthogonal Moments

0559878 - ÚTIA 2023 RIV CH eng J - Článek v odborném periodiku
Abdulhussain, S. H. - Mahmmod, B. M. - AlGhadhban, A. - Flusser, Jan
Face Recognition Algorithm Based on Fast Computation of Orthogonal Moments.
Mathematics. Roč. 10, č. 15 (2022), č. článku 2721. E-ISSN 2227-7390
Grant CEP: GA ČR GA21-03921S
Institucionální podpora: RVO:67985556
Klíčová slova: face recognition * orthogonal polynomials * orthogonal moments * feature extraction * block processing
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impakt faktor: 2.4, rok: 2022
Způsob publikování: Open access
http://library.utia.cas.cz/separaty/2022/ZOI/flusser-0559878.pdf https://www.mdpi.com/2227-7390/10/15/2721

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far. however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face image datasets, ORL and FEI. Different state-of-the-art face recognition methods were compared with the proposed method in order to evaluate its accuracy. We demonstrate that the proposed method achieves the highest recognition rate in different considered scenarios. Based on the obtained results, it can be seen that the proposed method is robust against noise and significantly outperforms previous approaches in terms of speed.
Trvalý link: https://hdl.handle.net/11104/0333425