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Face recognition in JPEG compressed domain: a novel coefficient selection approach

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Abstract

JPEG compression standard is widely used for reducing the volume of images that are stored or transmitted via networks. In biometrics datasets, facial images are usually stored in JPEG compressed format and should be fully decompressed to be used in a face recognition system. Recently, in order to reduce the computational complexity of JPEG decompression step, face recognition in compressed domain is considered as an emerging topic in face recognition systems. In this paper, a novel coefficient selection method based on face segmentation has been proposed for selecting a limited number of zigzag scanned quantized coefficients in JPEG compressed domain, which led to an improvement in recognition accuracy and a reduction in computational complexity of the face recognition system. In the proposed method, different low frequency coefficients based on the importance of the regions of a face have been selected for recognition process. The experiments were conducted on FERET and FEI face databases, and PCA and ICA methods have been utilized to extract the features of the selected coefficients. Different criteria including recognition accuracy and time complexity metrics were employed in order to evaluate the performance of the proposed method, and the results have been compared with those of the state-of-the art methods. The results show the superiority of the proposed approach, in terms of recognition ranks, discriminatory power and time complexity aspects.

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Acknowledgments

Portions of the research in this paper use the FERET database of facial images collected under the FERET program, sponsored by the DOD Counterdrug Technology Development Program Office. The authors would like to thanks NIST for providing FERET database and Laboratory of FEI in São Bernardo do Campo for providing FEI Brazilian face database.

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Authors and Affiliations

  1. ICT Research Institute, Tehran, Iran

    Mohammad-Shahram Moin

  2. Faculty of Electrical and Computer Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran

    Alireza Sepas-Moghaddam

Authors
  1. Mohammad-Shahram Moin
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  2. Alireza Sepas-Moghaddam
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Correspondence to Alireza Sepas-Moghaddam.

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Moin, MS., Sepas-Moghaddam, A. Face recognition in JPEG compressed domain: a novel coefficient selection approach. SIViP 9, 651–663 (2015). https://doi.org/10.1007/s11760-013-0492-8

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  • DOI: https://doi.org/10.1007/s11760-013-0492-8

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