Al-Thocb HSC: a harmony search algorithm for automated calibration of industrial equipment

Al-Thocb HSC: a harmony search algorithm for automated calibration of industrial equipment Calibration is an essential task for setting up camera parameters, especially when cameras are used for industrial applications like object recognition and picking that require a fine-grained location of the observed object. However, this process is time-consuming and requires specific image processing skills, which are not always available: an operator often needs to use the equipment rapidly without costly setup operations. The calibration system needs a coherent set of images of a given model, called a mire, positioned in different ways. In this paper, we propose to automate and to optimize the calibration system by eliminating the requirement for the user to select a suitable set of images. Thus, an optimized calibration can be obtained in a minimum of time. First, we propose to retrieve the set of points of each input image in order to avoid a renewed search at each calibration. Second, we define Al-Thocb, a Harmony Search Calibration algorithm, based on Harmony Search Optimization. The algorithm optimizes the selection of the best images. The satisfaction criterion is defined by a fitness function based on the projection error. The method allows to retrieve coherent camera parameters with no need for specific user skills. It also significantly improves the accuracy of calibration through the use of the reprojection error as fitness function. To demonstrate the applicability of Al-Thocb, we evaluate the accuracy and the responsiveness of the proposed algorithm and compare it to other existing methods. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Machine Vision and Applications Springer Journals

Al-Thocb HSC: a harmony search algorithm for automated calibration of industrial equipment

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2018 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Computer Science; Pattern Recognition; Image Processing and Computer Vision; Communications Engineering, Networks
ISSN
0932-8092
eISSN
1432-1769
D.O.I.
10.1007/s00138-018-0909-z
Publisher site
See Article on Publisher Site

Abstract

Calibration is an essential task for setting up camera parameters, especially when cameras are used for industrial applications like object recognition and picking that require a fine-grained location of the observed object. However, this process is time-consuming and requires specific image processing skills, which are not always available: an operator often needs to use the equipment rapidly without costly setup operations. The calibration system needs a coherent set of images of a given model, called a mire, positioned in different ways. In this paper, we propose to automate and to optimize the calibration system by eliminating the requirement for the user to select a suitable set of images. Thus, an optimized calibration can be obtained in a minimum of time. First, we propose to retrieve the set of points of each input image in order to avoid a renewed search at each calibration. Second, we define Al-Thocb, a Harmony Search Calibration algorithm, based on Harmony Search Optimization. The algorithm optimizes the selection of the best images. The satisfaction criterion is defined by a fitness function based on the projection error. The method allows to retrieve coherent camera parameters with no need for specific user skills. It also significantly improves the accuracy of calibration through the use of the reprojection error as fitness function. To demonstrate the applicability of Al-Thocb, we evaluate the accuracy and the responsiveness of the proposed algorithm and compare it to other existing methods.

Journal

Machine Vision and ApplicationsSpringer Journals

Published: Jan 29, 2018

References

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