Authors:
Patrick Spicer
;
Kristin Bohl
;
Gil Abramovich
and
Jacob Barhak
Affiliation:
NSF Engineering Research Center for Reconfigurable Manufacturing Systems, College of Engineering, University of Michigan, United States
Keyword(s):
Machine vision, Reconfigurable Systems, Camera Calibration, Multiple Cameras, Colour Recognition.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image Formation and Preprocessing
;
Image Formation, Acquisition Devices and Sensors
;
Multimodal and Multi-Sensor Models of Image Formation
;
Multi-View Geometry
Abstract:
This paper describes a Reconfigurable Array for Machine Vision Inspection (RAMVI) that is able to produce spatially-accurate images combining information obtained from several cameras. Automatic camera calibration is essential for minimizing the changeover time required to reconfigure the array. This paper describes an automatic calibration method that uses a colour coded calibration grid (CCG) to determine the field of view of each camera relative to the other cameras. Since colour is integral to the calibration process, robust colour recognition is essential, particularly since several cameras are involved. Hence, a rule-based colour recognition methodology is described. Results are presented demonstrating the effectiveness of this approach under varying lighting conditions.