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Color Constancy in RoboCup Robot Vision

Yasunori Takemura, Kazuo Ishii


One of the important subjects for mobile robots concerns about vision based decision-making system, where color constancy is a big problem for robots, as color property is often used to recognize their environments. Creatures can recognize color and shape of objects even if large changes of lighting conditions happen in such as outdoor environments. Biomimetic software and hardware attract attentions from the possibility to realize flexible and adaptive systems like creatures. We have been working on color constancy vision algorithms using bio-inspired information processing technique. In this paper, we evaluate the performances of color recognition using bio-inspired information processing algorithms: Self-Organizing Map (SOM), modular network SOM (mnSOM) and Neural Gas (NG), and discuss the experimental results in various light conditions.

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