Abstract:

A new biomimetic recognition method is proposed based on multidimensional space biomimetic informatics and multiresolution analysis. First, the multiscale features of samples are extracted by multiresolution analysis method and multiresolution robust representation at different scales are obtained by local histogram of oriented gradient descriptor. Second, the optimal multidimensional space covering of feature space is constructed by selforganizing map (SOM) clustering and distance projecting distribution in the feature space of same kind of samples. Finally, the sample to be identified is judged whether belongs to different scale covering sets to decide whether the sample comes from the same kind. To verify the effectiveness, the proposed method is applied to iris recognition. Receiver operating characteristic (ROC) curve and probability density function (PDF) of same and different class samples are given based on JLUIRIS database. Experimental results show the proposed method is effective for iris recognition application.

Key words: multidimensional space biomimetic informatics, biomimetic pattern recognition, multiresolution analysis, iris recognition