Face Recognition System Using Local Features Fusion for Multi-Masks

Abstract
Face recognition is a relatively novel research field, and its application is closely related to numerous other areas. Moreover, it is emerging as a critical research theme due to its broad range of applications. Thus, many face recognition methods use a variety of feature extraction approaches. Nonetheless, the issue continues to be challenging, particularly identifying non-biological entities. This paper proposes an extended descriptor for local features of an effectual facial recognition system using a local directional pattern operator. This technique combines the Frei-Chen and Robinson masks\' strengths by fusion of the directional features of LDP for these two masks; this elicits a robust feature extraction method for distinguishing faces. Experimental results using the Yale database show that the extended descriptor considerably improved recognition rate and better performance than traditional local feature descriptors.

Author
Mustafa Zuhaer Nayef Al-Dabagh

DOI
https://doi.org/10.1088/1742-6596/2107/1/012044

Publisher
Journal of Physics: Conference Series

ISSN

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