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Reduced complexity and optimized face recognition approach based on facial symmetry

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A Correction to this article was published on 09 July 2022

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Abstract

Recognition of face images is still a challenging and open research problem. A number of recent algorithms have shown that there is a vast scope in improving recognition accuracy by utilizing facial symmetry for face recognition task. The lower computational complexity and faster processing times make this method well suited for real-time applications. In this paper, we have used only one half of the face image for recognition task against various facial challenges. Keeping in view all the previous related studies that are limited in their scope, an unbiased comparison is presented between full face images and half face images by applying four subspace-based algorithms with four different distance metrics. Experiments are conducted on the two most challenging face databases. The FERET is a benchmark database, which closely simulates real-life scenarios, and LFW which is developed for the problem of unconstrained face recognition.

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Acknowledgements

This paper uses the FERET database of facial images collected under the FERET program, sponsored by the DOD counter drug technology development program office.

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Authors and Affiliations

  1. Department of Computer Science, Govt. Post Graduate College, Mansehra, Pakistan

    Waqas Ahmed

  2. Department of Computer Science, COMSATS University Islamabad, Lahore Campus, Islamabad, Pakistan

    Usama Ijaz Bajwa & Muhammad Waqas Anwar

  3. Department of Electrical Engineering, Mirpur University of Science and Technology (MUST), Mirpur, Azad Kashmir, Pakistan

    Muhammad Sajid

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  1. Waqas Ahmed
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  2. Usama Ijaz Bajwa
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  3. Muhammad Waqas Anwar
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  4. Muhammad Sajid
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Correspondence to Waqas Ahmed.

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Ahmed, W., Bajwa, U.I., Anwar, M.W. et al. Reduced complexity and optimized face recognition approach based on facial symmetry. J Real-Time Image Proc 19, 809–822 (2022). https://doi.org/10.1007/s11554-022-01224-0

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