NDLI: Finding the camera displacement in a 3D measurement system through matching the background texture of stereo images using hybrid GA

Content Provider	IEEE Xplore Digital Library
Author	Seyedin, S.A. Rezayi, H.
Copyright Year	2004
Description	Author affiliation: Electr. Eng. Dept., Ferdowsi Univ. of Mashhad, Iran (Seyedin, S.A.; Rezayi, H.)
Abstract	For 3D measurements using image processing system, one of the most important parameters that should be determined in a single camera parallel-axis system is the precise value of camera displacement. In this system when the camera is displaced, all image background points move with the same translation vector with respect to their initial positions in the first image without any other transformation. In this paper we propose a texture matching based technique for calculating this parameter. In this approach we find the best matching between the existent background textures in the stereo images with subpixel precision. This is accomplished by subpixel registration of texture areas. The subpixel image registration is formulated as a hybrid genetic optimization problem. The used genetic algorithm has the advantages of both classical (local) and global optimization algorithms. The precision of this method is 0.01 millimeter for determining the camera displacement.
Sponsorship	Syriatel Global Commun. Syrian Comput. Soc. Network HAMSHO Int. Phoenix Consulting DETECON: Detecon & Diebold Consultants Republique Francaise Ambassade de France en Syrie Syrian Airlines STE JUCI
Starting Page	361
Ending Page	362
File Size	233200
Page Count	2
File Format	PDF
ISBN	0780384822
DOI	10.1109/ICTTA.2004.1307779
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-04-23
Publisher Place	Syria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image registration Computer vision Actuators Image processing Machine vision Electric variables measurement Displacement measurement Cameras Stereo vision Genetic algorithms
Content Type	Text
Resource Type	Article

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