Pattern Recognition via PCNN and Tsallis Entropy.

Sensors (Basel)

School of Information Science and Engineering, Southeast University, P.R. China.

Published: November 2008

In this paper a novel feature extraction method for image processing via PCNN and Tsallis entropy is presented. We describe the mathematical model of the PCNN and the basic concept of Tsallis entropy in order to find a recognition method for isolated objects. Experiments show that the novel feature is translation and scale independent, while rotation independence is a bit weak at diagonal angles of 45° and 135°. Parameters of the application on face recognition are acquired by bacterial chemotaxis optimization (BCO), and the highest classification rate is 72.5%, which demonstrates its acceptable performance and potential value.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3787458PMC
http://dx.doi.org/10.3390/s8117518DOI Listing

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