Paper
28 December 1998 Stereo correspondence using geometric relational matching
Sekhavat Sharghi, Farhad A. Kamangar
Author Affiliations +
Proceedings Volume 3653, Visual Communications and Image Processing '99; (1998) https://doi.org/10.1117/12.334708
Event: Electronic Imaging '99, 1999, San Jose, CA, United States
Abstract
A new geometric relational matching approach is proposed to solve the stereo correspondence problem. The first distinct features are extracted in a pair of stereo images using a feature extractor. Then a newly developed window-based feature point detector is used to detect feature points from the extracted feature in both images. Feature points are connected with two points to form a straight line in both images. A match function representing the requirements of the epipola and disparity constraints in both images is proposed for straight line matching. Important information can be obtained from the parameter values attached to each line, such as distance and orientation. Information contained in the match function is used to determine straight-line correspondence. The method described here takes a unique approach to match straight lines. After that straight-line correspondence is established using the match function values in the left image and corresponding ones in the right image. Triplets of matched points are used to construct a model polygon in the left image. Then the entire right image is searched by an exhaustive search method to find a matching polygon. The computational complexity of the proposed method is proportional to the number of detected feature points in the image pair. Experimental results indicate that the method performs well for a variety of stereo images, and it is suitable for many applications.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sekhavat Sharghi and Farhad A. Kamangar "Stereo correspondence using geometric relational matching", Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); https://doi.org/10.1117/12.334708
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KEYWORDS
Image segmentation

Feature extraction

Lawrencium

Sensors

3D image processing

Image processing

Algorithm development

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