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Authors: Afra'a Ahmad Alyosef and Andreas Nürnberger

Affiliation: Otto von Guericke University Magdeburg, Germany

ISBN: 978-989-758-222-6

Keyword(s): SIFT Descriptor, RC-SIFT 64D, Feature Truncating, Properties of the SIFT Features, Image Near Duplicate Retrieval.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Feature Selection and Extraction ; Geometry and Modeling ; Image Understanding ; Image-Based Modeling ; Pattern Recognition ; Software Engineering ; Theory and Methods

Abstract: The scale invariant feature transformation algorithm (SIFT) has been widely used for near-duplicate retrieval tasks. Most studies and evaluations published so far focused on increasing retrieval accuracy by improving descriptor properties and similarity measures. Contrast, scale and orientation properties of the SIFT features were used in computing the SIFT descriptor, but their explicit influence in the feature matching step was not studied. Moreover, it has not been studied yet how to specify an appropriate criterion to extract (almost) the same number of SIFT features (respectively keypoints) of all images in a database. In this work, we study the effects of contrast and scale properties of SIFT features when ranking and truncating the extracted descriptors. In addition, we evaluate if scale, contrast and orientation features can be used to bias the descriptor matching scores, i.e., if the keypoints are quite similar in these features, we enforce a higher similarity in descriptor m atching. We provide results of a benchmark data study using the proposed modifications in the original SIFT􀀀128D and on the region compressed SIFT (RC-SIFT􀀀64D) descriptors. The results indicate that using contrast and orientation features to bias feature matching can improve near-duplicate retrieval performance. (More)

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Paper citation in several formats:
Ahmad Alyosef, A. and Nürnberger, A. (2017). The Effect of SIFT Features Properties in Descriptors Matching for Near-duplicate Retrieval Tasks.In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-222-6, pages 703-710. DOI: 10.5220/0006250607030710

@conference{icpram17,
author={Afra'a Ahmad Alyosef. and Andreas Nürnberger.},
title={The Effect of SIFT Features Properties in Descriptors Matching for Near-duplicate Retrieval Tasks},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2017},
pages={703-710},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006250607030710},
isbn={978-989-758-222-6},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - The Effect of SIFT Features Properties in Descriptors Matching for Near-duplicate Retrieval Tasks
SN - 978-989-758-222-6
AU - Ahmad Alyosef, A.
AU - Nürnberger, A.
PY - 2017
SP - 703
EP - 710
DO - 10.5220/0006250607030710

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