Automatic Construction of Accurate Image Processing using AdaBoost

Image processing and recognition technologies are required to solve various problems. We have already proposed the system which automatically constructs image processing with Genetic Programming (GP), Automatic Construction of Tree-structural Image Transformation (ACTIT). However, it is difficult to construct an accurate image processing for all training image sets if they have various characteristics. In this paper, we propose ACTIT-Boost which automatically constructs an accurate image processing by employing Adaptive Boosting (AdaBoost) to ACTIT. It learns training image sets and their areas which are difficultly approximated to target images in particular. We show experimentally that ACTIT-Boost is more effective in comparison with ordinary ACTIT.