Universiti Teknologi Malaysia Institutional Repository

Improved rotational matching of sift and surf

Goh, Kian Mau and Mohd. Mokji, Musa and Syed Abu Bakar, Syed Abdul Rahman (2012) Improved rotational matching of sift and surf. In: Fourth International Conference on Digital Image Processing (ICDIP 2012). SPIE, Bellingham, USA, pp. 1-6. ISBN 978-081948991-3

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Official URL: http://dx.doi.org/10.1117/12.953950


Scale-Invariant Feature Transform(SIFT) and Speeded-Up Robust Feature(SURF) are common techniques used for extracting robust features that can be used to perform matching between different viewpoints of scenes. Both methods basically involve three main stages, which are feature extraction, orientation assignment and feature descriptor extraction for matching. SURF is computation efficient compared to SIFT because the integral image is used for the convolutions to reduce computation time. However, both methods also do not focus much on the technique of matching. This paper introduces a method which can help to improve the rotational matching performance in term of accuracy by establishing a decision matrix and an approximated rotational angle within two corresponding images. The proposed method generally improved the matching rate around 10% to 20% in terms of accuracy.

Item Type:Book Section
Additional Information:Indexed by Scopus
Uncontrolled Keywords:descriptor, orientation, SIFT, SURF
Subjects:Q Science
Divisions:Biosciences and Bioengineering
ID Code:35809
Deposited On:11 Nov 2013 09:48
Last Modified:02 Feb 2017 05:27

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