Fuzzy neural networks in computer vision

Summary form only given, as follows. The emulation of human-like vision on a computer is often the desired goal of robot vision and medical image processing. Human vision possesses some important attributes such as perception and cognition. It is imperative that some aspects of these attributes be captured when emulating the human visual system. The processes of perception, mentation, and cognition imply that objects and images are not crisply perceived, and therefore the more common forms of logic such as binary cannot be used. The recently developed calculus of fuzzy logic along with neuron-like computational units appear to be very powerful tools for the emulation of human-like vision fields on a computer. A description is given of the connection between fuzzy logic and neural networks for the area of computer vision.<>