A handwritten character recognition algorithm based on artificial immune

Handwritten character recognition is an important research and application area on pattern recognition theory, which plays an important role on realizing automation of inputting character at all cases. In order to improve the rate of character recognition and decrease the time of recognition training, referencing to immune biological principle, a handwritten character recognition algorithm based on artificial immune is proposed. The antigen and memory cell in the artificial immune system are described. The equations of clone selection principle and of evolving memory cell are established. Finally, the process of character recognition is given. The experiment uses the well-know character set providing by F.Prat from UCI. The simulation results show that the method has faster speed and higher accuracy than the traditional handwritten recognition based on neural network. The algorithm steals the merit of self-adaptive learning, and immune memory in the biology immune system, which can also be applied to abnormity detection and pattern recognition.