Paper
8 May 2012 Adaptive error correction codes for face identification
Author Affiliations +
Abstract
Face recognition in uncontrolled environments is greatly affected by fuzziness of face feature vectors as a result of extreme variation in recording conditions (e.g. illumination, poses or expressions) in different sessions. Many techniques have been developed to deal with these variations, resulting in improved performances. This paper aims to model template fuzziness as errors and investigate the use of error detection/correction techniques for face recognition in uncontrolled environments. Error correction codes (ECC) have recently been used for biometric key generation but not on biometric templates. We have investigated error patterns in binary face feature vectors extracted from different image windows of differing sizes and for different recording conditions. By estimating statistical parameters for the intra-class and inter-class distributions of Hamming distances in each window, we encode with appropriate ECC's. The proposed approached is tested for binarised wavelet templates using two face databases: Extended Yale-B and Yale. We shall demonstrate that using different combinations of BCH-based ECC's for different blocks and different recording conditions leads to in different accuracy rates, and that using ECC's results in significantly improved recognition results.
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Wafaa R. Hussein, Harin Sellahewa, and Sabah A. Jassim "Adaptive error correction codes for face identification", Proc. SPIE 8406, Mobile Multimedia/Image Processing, Security, and Applications 2012, 84060B (8 May 2012); https://doi.org/10.1117/12.920567
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KEYWORDS
Facial recognition systems

Databases

Error analysis

Biometrics

Binary data

Computer programming

Discrete wavelet transforms

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