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http://dx.doi.org/10.9708/jksci.2011.16.7.105

Adaptive Segmentation Approach to Extraction of Road and Sky Regions  

Park, Kyoung-Hwan (Dept. of Computer Information Engineering, Kunsan National University)
Nam, Kwang-Woo (Dept. of Computer Information Engineering, Kunsan National University)
Rhee, Yang-Won (Dept. of Computer Information Engineering, Kunsan National University)
Lee, Chang-Woo (Dept. of Computer Information Engineering, Kunsan National University)
Publication Information
Journal of the Korea Society of Computer and Information / v.16, no.7, 2011 , pp. 105-115 More about this Journal
Abstract
In Vision-based Intelligent Transportation System(ITS) the segmentation of road region is a very basic functionality. Accordingly, in this paper, we propose a region segmentation method using adaptive pattern extraction technique to segment road regions and sky regions from original images. The proposed method consists of three steps; firstly we perform the initial segmentation using Mean Shift algorithm, the second step is the candidate region selection based on a static-pattern matching technique and the third is the region growing step based on a dynamic-pattern matching technique. The proposed method is able to get more reliable results than the classic region segmentation methods which are based on existing split and merge strategy. The reason for the better results is because we use adaptive patterns extracted from neighboring regions of the current segmented regions to measure the region homogeneity. To evaluate advantages of the proposed method, we compared our method with the classical pattern matching method using static-patterns. In the experiments, the proposed method was proved that the better performance of 8.12% was achieved when we used adaptive patterns instead of static-patterns. We expect that the proposed method can segment road and sky areas in the various road condition in stable, and take an important role in the vision-based ITS applications.
Keywords
ITS; Adaptive Pattern Extraction; Region Merge; Road Segmentation; Sky Segmentation;
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Times Cited By KSCI : 3  (Citation Analysis)
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