Efficient NCC-Based Image Matching in Walsh-Hadamard Domain View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2008

AUTHORS

Wei-Hau Pan , Shou-Der Wei , Shang-Hong Lai

ABSTRACT

In this paper, we proposed a fast image matching algorithm based on the normalized cross correlation (NCC) by applying the winner-update strategy on the Walsh-Hadamard transform. Walsh-Hadamard transform is an orthogonal transformation that is easy to compute and has nice energy packing capability. Based on the Cauchy-Schwarz inequality, we derive a novel upper bound for the cross-correlation of image matching in the Walsh-Hadamard domain. Applying this upper bound with the winner update search strategy can skip unnecessary calculation, thus significantly reducing the computational burden of NCC-based pattern matching. Experimental results show the proposed algorithm is very efficient for NCC-based image matching under different lighting conditions and noise levels. More... »

PAGES

468-480

Book

TITLE

Computer Vision – ECCV 2008

ISBN

978-3-540-88689-1
978-3-540-88690-7

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-88690-7_35

DOI

http://dx.doi.org/10.1007/978-3-540-88690-7_35

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1030878295


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