Pattern Recognition via PCNN and Tsallis Entropy
AbstractIn 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. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Zhang, Y.; Wu, L. Pattern Recognition via PCNN and Tsallis Entropy. Sensors 2008, 8, 7518-7529.
Zhang Y, Wu L. Pattern Recognition via PCNN and Tsallis Entropy. Sensors. 2008; 8(11):7518-7529.Chicago/Turabian Style
Zhang, YuDong; Wu, LeNan. 2008. "Pattern Recognition via PCNN and Tsallis Entropy." Sensors 8, no. 11: 7518-7529.