AN EFFECTIVE METHOD FOR IMAGE MATCHING BASED ON MODIFIED LBP AND SIFT

Yinan Wang, Nuo Zhang, Toshinori Watanabe, Hisashi Koga

Abstract

Scale Invariant Feature Transform (SIFT) is a very powerful and popular descriptor for image registration, which is commonly used in feature matching. However, there is still a need for improvement with respect to the matching accuracy of SIFT. In this paper, we present a combination of modified LBP and SIFT method for more reliable feature matching. The main idea of the proposed method is to extract spatially enhanced image features with modified Local Binary Pattern (LBP) from the images before implementation Difference-of-Gaussian (DoG) in SIFT. The proposed method is also robust to illumination changes, rotation and scaling of images. Experimental results show significant improvement over original SIFT.

References

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Paper Citation


in Harvard Style

Wang Y., Zhang N., Watanabe T. and Koga H. (2012). AN EFFECTIVE METHOD FOR IMAGE MATCHING BASED ON MODIFIED LBP AND SIFT . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-03-7, pages 410-413. DOI: 10.5220/0003827004100413


in Bibtex Style

@conference{visapp12,
author={Yinan Wang and Nuo Zhang and Toshinori Watanabe and Hisashi Koga},
title={AN EFFECTIVE METHOD FOR IMAGE MATCHING BASED ON MODIFIED LBP AND SIFT},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={410-413},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003827004100413},
isbn={978-989-8565-03-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)
TI - AN EFFECTIVE METHOD FOR IMAGE MATCHING BASED ON MODIFIED LBP AND SIFT
SN - 978-989-8565-03-7
AU - Wang Y.
AU - Zhang N.
AU - Watanabe T.
AU - Koga H.
PY - 2012
SP - 410
EP - 413
DO - 10.5220/0003827004100413