Fuzzy Logic, Neural Networks And Computer Vision

Madan M. Gupta

doi:10.1117/12.960296

27 March 1989 Fuzzy Logic, Neural Networks And Computer Vision

Madan M. Gupta

Proceedings Volume 1002, Intelligent Robots and Computer Vision VII; (1989) https://doi.org/10.1117/12.960296
Event: 1988 Cambridge Symposium on Advances in Intelligent Robotics Systems, 1988, Boston, MA, United States

Abstract

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 are 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. In this paper, we describe the connection between fuzzy logic and neural networks for the area of computer vision.

Citation Download Citation

Madan M. Gupta "Fuzzy Logic, Neural Networks And Computer Vision", Proc. SPIE 1002, Intelligent Robots and Computer Vision VII, (27 March 1989); https://doi.org/10.1117/12.960296

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