Abstract
Reichardt's elementary motion detectors are employed for detecting motion. Moving image-stationary background discrimination is realized by correlating the detected motion information with properly delayed visual afterimages. Fuzzy-set theory is used in a nonlinear integration algorithm for obtaining a moving object direction. Both hypothetical neural coding schemes of temporal coding and firing rate coding are used for representation of visual motion information. A biologically plausible electronic neural network setup has been built for real-time examination of proposed model. The simulation results could well explain the phenomenon of visual anti-camouflage. The proposed model may erect a bridge between natural vision and robot vision.
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