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Face Recognition Through Multi-Resolution Images

Face Recognition Through Multi-Resolution Images

Hazar Mliki, Emna Fendri, Ahmed Chebil
Copyright: © 2022 |Volume: 10 |Issue: 1 |Pages: 15
ISSN: 2166-7160|EISSN: 2166-7179|EISBN13: 9781683182832|DOI: 10.4018/IJSI.292018
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MLA

Mliki, Hazar, et al. "Face Recognition Through Multi-Resolution Images." IJSI vol.10, no.1 2022: pp.1-15. http://doi.org/10.4018/IJSI.292018

APA

Mliki, H., Fendri, E., & Chebil, A. (2022). Face Recognition Through Multi-Resolution Images. International Journal of Software Innovation (IJSI), 10(1), 1-15. http://doi.org/10.4018/IJSI.292018

Chicago

Mliki, Hazar, Emna Fendri, and Ahmed Chebil. "Face Recognition Through Multi-Resolution Images," International Journal of Software Innovation (IJSI) 10, no.1: 1-15. http://doi.org/10.4018/IJSI.292018

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Abstract

In this paper, we introduce a new method for face recognition in multi-resolution images. The proposed method is composed of two phases: an off-line phase and an inference phase. In the off-line phase, we built the Kernel Partial Least Squares (KPLS) regression model to map the LR facial features to HR ones. The KPLS predictor was then used in the inference phase to map HR features from LR features. We applied in both phases the Block-Based Discrete Cosine Transform (BBDCT) descriptor to enhance the facial feature description. Finally, the identity matching was carried out with the K-Nearest Neighbor (KNN) classifier. Experimental study was conducted on the AR and ORL databases and the obtained results proved the efficiency of the proposed method to deal with LR and VLR face recognition problem.

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