An Improved LNMF Approach for Palmprint Recognition

An improved local non-negative matrix factorizetion (LNMF) algorithm for palmprint recognition is proposed to solve the problem regarding the high requirements of palmprint image preprocessing. First, the Fisher discriminant criterion is integrated into the non-negative matrix algorithm of the target function, using the gradient descent method. To solve the drawbacks of the traditional algorithm, the LNMF algorithm does not contain class information affecting the recognition rate, and finally, it chooses the appropriate classifier for matching. Experiments on two databases are conducted, and the results show that the proposed method has very high recognition rates on the two databases. In a comparison with other algorithms, the current algorithm achieves a higher recognition effect.