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Real-Time Facial Recognition Using Deep Learning and Local Binary Patterns

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Proceedings of International Ethical Hacking Conference 2018

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 811))

Abstract

Today, surveillance is everywhere where the operators continuously observe the video captured by the camera to identify the human/object for public safety. Automated systems are being developed for real-time facial recognition as it is highly difficult for the operators to track and identify in highly crowded areas. The feature selection process is generally used to represent faces, and a machine learning-based approach is used to classify the faces in face recognition. A variety of poses, expressions and illumination conditions make the manual feature selection process error-prone and computationally complex. This paper proposes a less computationally complex real-time face recognition algorithm and system based on local binary patterns and convolutional neural networks (CNNs). A modified version of LENET is used instead for face recognition. The recognition accuracy of the proposed method is tested on two publicly available datasets. A new database covering most of the challenges like illumination and oriental variations, facial expressions, facial details (goggles, beard and turban) and age factor is also developed. The proposed architecture proved accurate up to 97.5% in offline mode and an average accuracy of 96% in the real-time recognition process. In the real-time process, frame reading and frame processing are done in two separate threads to improve the frame rate from 28 to 38 FPS.

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Authors and Affiliations

  1. ECE Department, GITAM University-Bengaluru Campus, Bengaluru, India

    B. Venkata Kranthi

  2. ECE Department, K. S. Institute of Technology, Kanakapura Road, Bengaluru, India

    Borra Surekha

Authors
  1. B. Venkata Kranthi
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  2. Borra Surekha
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Corresponding author

Correspondence to B. Venkata Kranthi .

Editor information

Editors and Affiliations

  1. Department of Information Technology, Institute of Engineering and Management, Kolkata, India

    Mohuya Chakraborty

  2. Institute of Engineering and Management, Kolkata, India

    Satyajit Chakrabarti

  3. Department of Automation and Applied Informatics, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  4. Department of Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India

    J. K. Mandal

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Venkata Kranthi, B., Surekha, B. (2019). Real-Time Facial Recognition Using Deep Learning and Local Binary Patterns. In: Chakraborty, M., Chakrabarti, S., Balas, V., Mandal, J. (eds) Proceedings of International Ethical Hacking Conference 2018. Advances in Intelligent Systems and Computing, vol 811. Springer, Singapore. https://doi.org/10.1007/978-981-13-1544-2_27

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  • DOI: https://doi.org/10.1007/978-981-13-1544-2_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1543-5

  • Online ISBN: 978-981-13-1544-2

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