Share Email Print
cover

Proceedings Paper

Dynamic template size control in digital image correlation based strain measurements
Author(s): Janne Koljonen; Olli Kanniainen; Jarmo T. Alander
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Image matching is a common procedure in computer vision. Usually the size of the image template is fixed. If the matching is done repeatedly, as e.g. in stereo vision, object tracking, and strain measurements, it is beneficial, in terms of computational cost, to use as small templates as possible. On the other hand larger templates usually give more reliable matches, unless e.g. projective distortions become too great. If the template size is controlled locally dynamically, both computational efficiency and reliability can be achieved simultaneously. Adaptive template size requires though that a larger template can be sampled anytime. This paper introduces a method to adaptively control the template size in a digital image correlation based strain measurement algorithm. The control inputs are measures of confidence of match. Some new measures are proposed in this paper, and the ones found in the literature are reviewed. The measures of confidence are tested and compared with each other as well as with a reference method using templates of fixed size. The comparison is done with respect to computational complexity and accuracy of the algorithm. Due to complex inter-actions of the free parameters of the algorithm, random search is used to find an optimal parameter combination to attain a more reliable comparison. The results show that with some confidence measures the dynamic scheme outperforms the static reference method. However, in order to benefit from the dynamic scheme, optimization of the parameters is needed.

Paper Details

Date Published: 10 September 2007
PDF: 12 pages
Proc. SPIE 6764, Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision, 67640L (10 September 2007); doi: 10.1117/12.732355
Show Author Affiliations
Janne Koljonen, Univ. of Vaasa (Finland)
Olli Kanniainen, Univ. of Vaasa (Finland)
Jarmo T. Alander, Univ. of Vaasa (Finland)


Published in SPIE Proceedings Vol. 6764:
Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision
David P. Casasent; Ernest L. Hall; Juha Röning, Editor(s)

© SPIE. Terms of Use
Back to Top