Ear recognition based on improved NMFSC
基于改进NMFSC方法的人耳识别

Based on ear recognition, an improved NMFSC(Non-negative Matrix Factorization with Sparseness Constraints) method was proposed by imposing an additional constraint on the objective function of NMFSC, which could capture the semantic relations of coefficient matrix as orthogonal as possible. The interated rules to solve the objective function with the constraint were presented, and its convergence was proved. The suitable weights were chosen for sub-region based on class-cluster rule, which could get the optimal mapping overall similarity from sub-region similarity. The experiment results show that the proposed method can obtain better performance.