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http://dx.doi.org/10.5394/KINPR.2008.32.5.355

A Study on Genetic Algorithm and Stereo Matching for Object Depth Recognition  

Hong, Seok-Keun (Dept of Control & Instrumentation Engineering., National Korea Maritime University)
Cho, Seok-Je (Division of Computer.Control and Electronic Communications, National Korea Maritime University)
Publication Information
Journal of Navigation and Port Research / v.32, no.5, 2008 , pp. 355-361 More about this Journal
Abstract
Stereo matching is one of the most active research areas in computer vision. In this paper, we propose a stereo matching scheme using genetic algorithm for object depth recognition. The proposed approach considers the matching environment as an optimization problem and finds the optimal solution by using an evolutionary strategy. Accordingly, genetic operators are adapted for the circumstances of stereo matching. An individual is a disparity set. Horizontal pixel line of image is considered as a chromosome. A cost function is composed of certain constraints which are commonly used in stereo matching. Since the cost function consists of intensity, similarity and disparity smoothness, the matching process is considered at the same time in each generation. The LoG(Laplacian of Gaussian) edge is extracted and used in the determination of the chromosome. We validate our approach with experimental results on stereo images.
Keywords
Stereo matching; genetic algorithm; disparity map; genetic operator; Edge information;
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