Human-imitation recognition algorithm based on multi-character

A multi-character recognition method based on hidden Markov model (HMM) was presented. The method can reduce the calculation load of correlation and improve recognition accuracy compared with single-character recognition in video. The characteristics used for recognizing include the shape character, the color character, the texture character and so on. Even our human being generally uses these characteristics to recognize objects in practice. A recognition experiment of 17 fishes was carried out in the paper. The experimental results demonstrate the high veracity of the multi-character recognition algorithm. Together with the tracking process, it can handle dynamic objects, so the multi-character recognition is more like the human recognition, and has great application value.