Comparison and Combination of Ear and Face Images in Appearance-Based Biometrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Force field feature extraction for ear biometrics
Computer Vision and Image Understanding
Multi-view ear recognition based on moving least square pose interpolation
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Face authentication with Gabor information on deformable graphs
IEEE Transactions on Image Processing
Gabor-Based Region Covariance Matrices for Face Recognition
IEEE Transactions on Circuits and Systems for Video Technology
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Based on force field convergence map and Log-Gabor filter, a novel multi-view ear feature extraction approach is proposed. This work first introduces the basic concepts and principles of force field transformation. Then a discussion on why force field convergence map rather than force field transformation is more suitable for multi-view ear feature extraction is given. After getting multi-view ear force field convergence map, Log-Gabor filter is applied to extract multiple scale and multiple orientation features. Finally, to verify the effectiveness of the proposed feature extraction method, different classifiers and different multi-view ear dataset are well utilized, to perform multi-view ear classification task. Experimental results and comparisons show the efficiency and the superiority of the proposed convergence map with the Log-Gabor filter method.