High-performance pattern recognition system using an improved neural classification chain and decision fusion on multispectral information

The performance level of pattern recognition (PR) systems can be improved using in a proper way new powerful artificial neural networks inside of its classification chains and respectively, decision fusion techniques on available multispectral information. Consequently, to increase the pattern recognition performances, an improved neural classification chain and respectively, an evolutive version of Sugeno´s fuzzy integral based on high-resolution radar (HRR), video and thermal imagery use are described. To confirm the broached theoretical aspects, a real image database was used.