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In this paper, a novel feature fusion method based on kernel canonical correlation analysis (KCCA) is presented and applied to ear and profile face based multimodal biometrics for personal recognition. Ear recognition is proved to be a new and promising authentication technique. The fusion of ear and face biometrics could fully utilize their connection(More)
This paper proposes a novel method based on Haar wavelet transform and uniform local binary patterns (ULBPs) to recognize ear images. Firstly, ear images are decomposed by Haar wavelet transform. Then ULBPs are combined simultaneously with block-based and multi-resolution methods to describe together the texture features of ear sub-images transformed by(More)
An improved non-negative matrix factorization with sparseness constraints (INMFSC) is proposed by imposing an additional constraint on the objective function of NMFSC, which can control the sparseness of both the basis vectors and the coefficient matrix simultaneously. The update rules to solve the objective function with constraints are presented. Research(More)
Ear recognition is proved to be a new and promising authentication technique. Because of ear's special physiological structure and location, it is reasonable to combine ear with profile face for recognition in such scenarios as frontal face images are not available. In this paper, a novel non-intrusive multimodal recognition technology based on ear and(More)
Current research on ear recognition in 2D achieves good performance in constrained environments. However the recognition performance degrades severely under occlusion, noise or pose, illumination variations. This paper proposes a 2D ear recognition approach based on sparse representation to deal with ear recognition under partial occlusion. Firstly, the ear(More)
Ear recognition is a new research area in the computer vision and pattern recognition field. This paper proposes a new ear biometrics system-compound structure classifier system for ear recognition (CSCSER), based on the research of ear recognition with algebraic feature. The system first makes rough classification to the human ears according to their(More)
Although ear recognition has been researched widely, there still exist some problems to be resolved in depth such as multi-pose ear recognition which is rarely focused on. In this paper, different from previous methods used for ear recognition, one nonlinear algorithm, called locally linear embedding (LLE) belonging to manifold learning technique is(More)