Hybrid machine vision method for autonomous guided vehicles

Jian Lu; Kyoko Hamajima; Koji Ishihara

doi:10.1117/12.474027

22 May 2003 Hybrid machine vision method for autonomous guided vehicles

Jian Lu, Kyoko Hamajima, Koji Ishihara

Proceedings Volume 5011, Machine Vision Applications in Industrial Inspection XI; (2003) https://doi.org/10.1117/12.474027
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

As a prospective intelligent sensing method for Autonomous Guided Vehicle (AGV), machine vision is expected to have balanced ability of covering a large space and also recognizing details of important objects. For this purpose, the proposed hybrid machine method here combines the stereo vision method and the traditional 2D method. The former implements coarse recognition to extract object over a large space, and the later implement fine recognition about some sub-areas corresponding to important and/or special objects. This paper is mainly about the coarse recognition. In order to extract objects in the coarse recognition stage, the disparity image calculated according to stereo vision principle is segmented by two consequent steps of region expansion and convex split. Then the 3D measurement about the rough positions and sizes of extracted objects is performed according to the disparity information of the corresponding segmentation, and is used for recognizing the objects' attributes by means of pattern learning/recognition. The attribute information resulted is further used to assist fine recognition in the way of performing gaze control to input suitable image of the interested objects, or to directly control AGV's travel. In our example AGV application, some navigation-signs are introduced to indicate the travel route. When the attribute shows that the object is a navigation-sign, the 3D measurement is used to gaze the navigation-sign, in order for the fine recognition to analyze the specific meaning by means of traditional 2D method.

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Jian Lu, Kyoko Hamajima, and Koji Ishihara "Hybrid machine vision method for autonomous guided vehicles", Proc. SPIE 5011, Machine Vision Applications in Industrial Inspection XI, (22 May 2003); https://doi.org/10.1117/12.474027

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KEYWORDS

Image segmentation

3D metrology

Machine vision

Cameras

Calibration

Image processing

3D image processing

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