Title: Face recognition using threshold string representation matching under unconstrained conditions

Authors: Manisha Kumari Meena; Hemant Kumar Meena; Srikanta Patnaik; Gurpinder Singh

Addresses: Department of Electrical Engineering, MNIT Jaipur, Jaipur, India ' Department of Electrical Engineering, MNIT Jaipur, Jaipur, India ' Department of Computer Science Engineering, IIMT, Bhubaneswar, India ' Department of Electrical Engineering, MNIT Jaipur, Jaipur, India

Abstract: This paper introduces a new approach called the threshold string representation matching (TSRM) algorithm, designed to enhance face identification and verification in scenarios by partial occlusions like sunglasses, scarves, and caps. The TSRM algorithm innovatively manipulates pixel features by calculating the difference between the centre pixel and its neighbours rather than relying on the traditional feature compression method (CSM-RL), where pixel difference is taken row-wise. This technique also improves the robustness of facial expression recognition by focusing on localised spatial relationships within the image patches. Our algorithm provides a novel feature-matching algorithm which effectively matches the prob image with the gallery image in the occlusion condition. We evaluated our proposed TSRM approach on two public face datasets: the AR dataset, which includes natural occlusion, and the ORL dataset, for synthetic occlusion.

Keywords: partial occlusion; face recognition; the difference between patches; k-means clustering; threshold string representation method; TSRM.

DOI: 10.1504/IJISTA.2025.148889

International Journal of Intelligent Systems Technologies and Applications, 2025 Vol.23 No.3, pp.319 - 336

Received: 14 Jun 2024
Accepted: 16 Dec 2024
Published online: 30 Sep 2025 *

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