Abstract
This paper proposes an algorithm for efficient and exhaustive template matching based on the Zero mean Normalized Cross Correlation (ZNCC) function. The algorithm consists in checking at each position a sufficient condition capable of rapidly skipping most of the expensive calculations involved in the evaluation of ZNCC scores at those points that cannot improve the best score found so far. The sufficient condition devised in this paper extends the concept of Bounded Partial Correlation (BPC) from Normalized Cross Correlation (NCC) to the more robust ZNCC function. Experimental results show that the proposed technique is effective in speeding up the standard procedure and that the behavior, in term of computational savings, follows that obtained by the BPC technique in the NCC case.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gottesfeld Brown, L.: A survey of image registration techniques. ACM Computing Surveys 24, 325–376 (1992)
Krattenthaler, W., Mayer, K.J., Zeiler, M.: Point correlation: a reduced-cost templa tematching technique. In: 1st IEEE Int. Conf. on Image Processing (ICIP 1994), Austin, Texas, USA, September 1994, vol. I, pp. 208–212 (1994)
Rosenfeld, A., Vanderburg, G.J.: Coarse-Fine template matching. IEEE Trans. on Sys. Man and Cyb. 7, 104–197 (1977)
Rosenfeld, A., Vanderburg, G.J.: Two-stage template matching. IEEE Trans. on Image Processing 26, 384–393 (1977)
Di Stefano, L., Mattoccia, S.: Fast Template Matching using Bounded Partial Correlation. Machine Vision and Applications 13, 213–221 (2003)
Di Stefano, L., Mattoccia, S.: A sufficient condition based on the Cauchy-Schwarz inequality for efficient Template Matching. In: IEEE Int. Conf. on Image Processing (ICIP 2003), Barcelona, Spain, September 14-17 (2003)
Mc Donnell, M.J.: Box-Filtering Techniques. Computer Graphics and Image Processing 17, 65–70 (1981)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Di Stefano, L., Mattoccia, S., Tombari, F. (2004). An Algorithm for Efficient and Exhaustive Template Matching. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30125-7_51
Download citation
DOI: https://doi.org/10.1007/978-3-540-30125-7_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23223-0
Online ISBN: 978-3-540-30125-7
eBook Packages: Springer Book Archive