Biological information fusion using a PCNN and belief filtering

The paper focuses on extracting and fusing visual feature information to discern targets much like a human fuses visual, auditory, and somatosensory data. Extraction of features is performed using a Pulse Coupled Neural Network to simulate visual-cortex processing of linking related-feature information. The feature-based biological sensor fusion approach extracts features from images, associates relevant features, and uses a belief filter to confirm or deny target identity.