Transform Based Feature Extraction and Dimensionality Reduction Techniques

Abstract

Various changes in illumination, expression, viewpoint, and plane rotation present challenges to face recognition. Low dimensional feature representation with enhanced discrimination power is of paramount importance to face recognition system. This chapter presents transform based techniques for extraction of efficient and effective features to solve some of the challenges in face recognition. The techniques are based on the combination of Radon transform, Discrete Cosine Transform (DCT), and Discrete Wavelet Transform (DWT). The property of Radon transform to enhance the low frequency components, which are useful for face recognition, has been exploited to derive the effective facial features. The comparative study of various transform based techniques under different conditions like varying illumination, changing facial expressions, and in-plane rotation is presented in this chapter. The experimental results using FERET, ORL, and Yale databases are also presented in the chapter.