1 April 2009 Wavelet-based illumination invariant preprocessing in face recognition
Goh Yi Zheng, Andrew Beng Jin Teoh, Michael Goh Kah Ong
Author Affiliations +
Abstract
Performance of a contemporary two-dimensional face-recognition system has not been satisfied due to the variation in lighting. As a result, many works of solving illumination variation in face recognition have been carried out in past decades. Among them, the Illumination-Reflectance model is one of the generic models that is used to separate the individual reflectance and illumination components of an object. The illumination component can be removed by means of image-processing techniques to regain an intrinsic face feature, which is depicted by the reflectance component. We present a wavelet-based illumination invariant algorithm as a preprocessing technique for face recognition. On the basis of the multiresolution nature of wavelet analysis, we decompose both illumination and reflectance components from a face image in a systematic way. The illumination component wherein resides in the low-spatial-frequency subband can be eliminated efficiently. This technique works out very advantageously for achieving higher recognition performance on YaleB, CMU PIE, and FRGC face databases.
©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)
Goh Yi Zheng, Andrew Beng Jin Teoh, and Michael Goh Kah Ong "Wavelet-based illumination invariant preprocessing in face recognition," Journal of Electronic Imaging 18(2), 023001 (1 April 2009). https://doi.org/10.1117/1.3112004
Published: 1 April 2009
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CITATIONS
Cited by 14 scholarly publications.
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KEYWORDS
Wavelets

Databases

Reflectivity

Facial recognition systems

Discrete wavelet transforms

Light sources and illumination

Image filtering

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