Matching segments in stereoscopic vision

Author

Loaiza, Humberto ; Triboulet, Jean ; Lelandais, Sylvie ; Barat, Christian

Volume

4

Issue

1

fYear

2001

fDate

3/1/2001 12:00:00 AM

Firstpage

37

Lastpage

42

Abstract

We have shown that it´s possible to realize a stereoscopic sensor with poor cameras. We developed image processing that is robust and allows us to quickly obtain results for the matching algorithm. We computed an important number of features on each segment, and with these features, we built 16-component vector used in the classification step. After an exhaustive study, we decided to combine two methods, Bayesian and neural, to construct an efficient classifier. The tests for indoor images had better than 90% good matching. With segment couples, it is possible to compute the 3D coordinates of the objects. Therefore, the mobile robot is able to localize and move about in the environment

Keywords

calibration; image classification; image matching; mobile robots; robot vision; stereo image processing; 16-component vector; 3D coordinates; Bayesian method; classification step; image processing; indoor images; matching algorithm; mobile robot; neural net; stereoscopic vision; Coordinate measuring machines; Digital cameras; Histograms; Image processing; Image segmentation; Instruments; Length measurement; Pixel; Retina; Table lookup;

fLanguage

English

Journal_Title

Instrumentation & Measurement Magazine, IEEE

Publisher

ieee

ISSN

1094-6969

Type

jour

DOI

10.1109/5289.911172

Filename

911172