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Proceedings Paper

Local directional pattern of phase congruency features for illumination invariant face recognition
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Paper Abstract

An illumination-robust face recognition system using Local Directional Pattern (LDP) descriptors in Phase Congruency (PC) space is proposed in this paper. The proposed Directional Pattern of Phase Congruency (DPPC) is an oriented and multi-scale local descriptor that is able to encode various patterns of face images under different lighting conditions. It is constructed by applying LDP on the oriented PC images. A LDP feature is obtained by computing the edge response values in eight directions at each pixel position and encoding them into an eight bit binary code using the relative strength magnitude of these edge responses. Phase congruency and local directional pattern have been independently used in the field of face and facial expression recognition, since they are robust to illumination changes. When the PC extracts the discontinuities in the image such as edges and corners, the LDP computes the edge response values in different directions and uses these to encode the image texture. The local directional pattern descriptor on the phase congruency image is subjected to principal component analysis (PCA) for dimensionality reduction for fast and effective face recognition application. The performance evaluation of the proposed DPPC algorithm is conducted on several publicly available databases and observed promising recognition rates. Better classification accuracy shows the superiority of the LDP descriptor against other appearance-based feature descriptors such as Local Binary Pattern (LBP). In other words, our result shows that by using the LDP descriptor the Euclidean distance between reference image and testing images in the same class is much less than that between reference image and testing images from the other classes.

Paper Details

Date Published: 5 May 2014
PDF: 8 pages
Proc. SPIE 9094, Optical Pattern Recognition XXV, 90940G (5 May 2014); doi: 10.1117/12.2050835
Show Author Affiliations
Almabrok E. Essa, Univ. of Dayton (United States)
Vijayan K. Asari, Univ. of Dayton (United States)

Published in SPIE Proceedings Vol. 9094:
Optical Pattern Recognition XXV
David Casasent; Tien-Hsin Chao, Editor(s)

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