Title: A new scene analysis using genetic algorithm based fuzzy ID3 method
Authors: Chang, JY
Cho, CW
電控工程研究所
Institute of Electrical and Control Engineering
Issue Date: 2005
Abstract: In this paper, we utilize a neural network based machine learning algorithm to segment natural objects in outdoor scene images. We have developed a genetic algorithm based fuzzy ID3 method, which can build a fuzzy decision tree to summarize the regularities existing in the data set. Using this method, we then propose a road scene analysis system, by which natural element segmentation rules can be learned from several road scene images. In the image analysis phase, the natural element regions are obtained through inference on these learned rules. Moreover, we can apply image groundtruthing to further improve the classification accuracy. The testing results have demonstrated that the object segmentation accuracy is quite high.
URI: http://hdl.handle.net/11536/17638
ISBN: 0-7803-9048-2
ISSN: 1098-7576
Journal: Proceedings of the International Joint Conference on Neural Networks (IJCNN), Vols 1-5
Begin Page: 1770
End Page: 1775
Appears in Collections:Conferences Paper