Abstract
The project is aimed at developing new person recognition algorithm, which deals with the problems using matching of filtered histograms of oriented gradients computed in circular sliding windows and using inverted index of histograms for efficient image retrieval. The project results have various scientific, industry and social applications, which require automatic non-cooperative indoors and outdoors person recognition at a distance using multimodal biometrics extracted from multisensory noisy data. For instance, new security and surveillance systems working under in open weather could be developed based on the proposed methods. The performance of the proposed person recognition algorithm in the actual environment is presented and discussed. The results of computer simulation obtained with the proposed algorithm are compared to those of available algorithms in terms of matching accuracy and processing time.
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