Simplified Gabor wavelets for human face recognition

Authors:
Wing-Pong Choi;Siu-Hong Tse;Kwok-Wai Wong;Kin-Man Lam
Affiliations:
Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Venue:
Pattern Recognition
Year:
2008

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Abstract

Gabor wavelets (GWs) are commonly used for extracting local features for various applications such as object detection, recognition and tracking. However, extracting Gabor features is computationally intensive, so the features are impractical for real-time applications. In this paper, we propose a simplified version of Gabor wavelets (SGWs) and an efficient algorithm for extracting the features based on an integral image. We evaluate the performance of the SGW features for face recognition. Experimental results show that using SGWs can achieve a performance level similar to using GWs, while the runtime for feature extraction using SGWs is, at most, 4.39 times faster than that of GWs implemented by using the fast Fourier transform (FFT).