Adaptive color calibration algorithm using brain inspired technology

One of important subjects for mobile robots is the vision based decision making system, where the color constancy is big problem for robots which use color property to recognize environments. We have been working on color constancy vision algorithms using bio-inspired information processing as creatures can recognize color and shape of objects even if there exits a large change of light conditions in outdoor environments. We evaluate the performances of color recognition using brain-inspired processing algorithms such as Self-Organizing Map (SOM), modular network SOM (mnSOM) and Neural Gas (NG). In this paper, the experimental results in dynamical conditions are discussed.