Title: Illumination identification by using image colour data and robot's location and orientation data
Authors: Michael S. Zehmeister, Yang Sok Kim, Byeong Ho Kang
Addresses: School of Computing and Information Systems, University of Tasmania, Sandy Bay, TAS, 7001, Australia. ' School of Computing and Information Systems, University of Tasmania, Sandy Bay, TAS, 7001, Australia. ' School of Computing and Information Systems, University of Tasmania, Sandy Bay, TAS, 7001, Australia
Abstract: Lighting changes render colour calibrations inaccurate and effectively blind systems that rely on identifying objects by colour. This study investigates the relationships in the colour data of image pixels between lighting conditions in an effort to identify trends that can be used as the basis of a rule-based system. The aim of the system is to identify the current lighting level as one of a set of known conditions. The proposed system uses both the colour data of image pixels and location and orientation information of Artificial Intelligence roBOt (AIBO, homonymous with |partner| in Japanese) to identify lighting levels, allowing a vision system to switch to an appropriate pre-configured calibration. While the direct area application is on AIBO in the RoboCup domain, the work is applicable in any area that uses color-vision in a situation in which lighting changes occur.
Keywords: illumination identification; colour calibrations; AIBO; artificial intelligence roBOt; RoboCup; image colour data; lighting changes; robot vision; robot location; robot orientation.
International Journal of Ad Hoc and Ubiquitous Computing, 2009 Vol.4 No.1, pp.13 - 23
Published online: 09 Dec 2008 *Full-text access for editors Access for subscribers Purchase this article Comment on this article