@article {IOPORT.05832601,
    author       = {Zhou, Xin and Yang, Ni-Qing and Wu, Xiao-Juan and Zhang, Xiao-Yan and Wang, Xiao-Gang},
    title        = {Human-imitation recognition algorithm based on multi-character.},
    year         = {2009},
    journal      = {Journal of Shanghai Jiaotong University (Science)},
    volume       = {14},
    number       = {5},
    issn         = {1007-1172},
    pages        = {526-530},
    publisher    = {Shanghai Jiaotong University, Shanghai; Springer, Heidelberg},
    doi          = {10.1007/s12204-009-0526-0},
    abstract     = {Summary: A multi-character recognition method based on a hidden Markov model (HMM) is 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 is 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.},
    identifier   = {05832601},
}