Biomimetic Pattern Recognition Based on the Young-Helmholtz Model of Multispectral Image

Biomimetic pattern recognition aim at finding the best coverage of per kind of sample´s distribution in the feature space. It is based on the analysis of relationship of sample points in the feature space. According to the principle of ¿same source¿, research the same kind of samples´ distribution in the feature space can get eigenvector information with low data amount. This can be realized by `coverage recognizing method of complex geometric body in high dimensional space´. Self-adaptive topological structure of high dimensional geometrical neuron model offers theoretical basis for its realization. In this paper, we propose biomimetic pattern recognition theory based on the Young-Helmholtz model of multispectral images, and study its algorithm. The experiment result proves the efficiency of our theory.