19 February 2013 Robust face recognition algorithm for identifition of disaster victims
Author Affiliations +
Abstract
We present a robust face recognition algorithm for the identification of occluded, injured and mutilated faces with a limited training set per person. In such cases, the conventional face recognition methods fall short due to specific aspects in the classification. The proposed algorithm involves recursive Principle Component Analysis for reconstruction of afiected facial parts, followed by a feature extractor based on Gabor wavelets and uniform multi-scale Local Binary Patterns. As a classifier, a Radial Basis Neural Network is employed. In terms of robustness to facial abnormalities, tests show that the proposed algorithm outperforms conventional face recognition algorithms like, the Eigenfaces approach, Local Binary Patterns and the Gabor magnitude method. To mimic real-life conditions in which the algorithm would have to operate, specific databases have been constructed and merged with partial existing databases and jointly compiled. Experiments on these particular databases show that the proposed algorithm achieves recognition rates beyond 95%.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wouter J. R. Gevaert, Wouter J. R. Gevaert, Peter H. N. de With, Peter H. N. de With, } "Robust face recognition algorithm for identifition of disaster victims", Proc. SPIE 8655, Image Processing: Algorithms and Systems XI, 865503 (19 February 2013); doi: 10.1117/12.2001634; https://doi.org/10.1117/12.2001634
PROCEEDINGS
11 PAGES


SHARE
Back to Top