loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Richard Connor 1 ; Stewart MacKenzie-Leigh 1 ; Franco Alberto Cardillo 2 and Robert Moss 1

Affiliations: 1 University of Strathclyde, United Kingdom ; 2 Consiglio Nazionale delle Ricerche, Italy

ISBN: 978-989-758-090-1

Keyword(s): Near-duplicate Image Detection, Benchmark, Image Similarity Function, Forensic Image Detection.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Multimedia Forensics

Abstract: There are many contexts where the automated detection of near-duplicate images is important, for example the detection of copyright infringement or images of child abuse. There are many published methods for the detection of similar and near-duplicate images; however it is still uncommon for methods to be objectively compared with each other, probably because of a lack of any good framework in which to do so. Published sets of near-duplicate images exist, but are typically small, specialist, or generated. Here, we give a new test set based on a large, serendipitously selected collection of high quality images. Having observed that the MIR-Flickr 1M image set contains a significant number of near-duplicate images, we have discovered the majority of these. We disclose a set of 1,958 near-duplicate clusters from within the set, and show that this is very likely to contain almost all of the near-duplicate pairs that exist. The main contribution of this publication is the identification of these images, which may then be used by other authors to make comparisons as they see fit. In particular however, near-duplicate classification functions may now be accurately tested for sensitivity and specificity over a general collection of images. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 34.229.113.106

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Connor, R.; Connor, R.; MacKenzie-Leigh, S.; Cardillo, F. and Moss, R. (2015). Identification of MIR-Flickr Near-duplicate Images - A Benchmark Collection for Near-duplicate Detection.In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-090-1, pages 565-571. DOI: 10.5220/0005359705650571

@conference{visapp15,
author={Richard Connor. and Richard Connor. and Stewart MacKenzie{-}Leigh. and Franco Alberto Cardillo. and Robert Moss.},
title={Identification of MIR-Flickr Near-duplicate Images - A Benchmark Collection for Near-duplicate Detection},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={565-571},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005359705650571},
isbn={978-989-758-090-1},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015)
TI - Identification of MIR-Flickr Near-duplicate Images - A Benchmark Collection for Near-duplicate Detection
SN - 978-989-758-090-1
AU - Connor, R.
AU - Connor, R.
AU - MacKenzie-Leigh, S.
AU - Cardillo, F.
AU - Moss, R.
PY - 2015
SP - 565
EP - 571
DO - 10.5220/0005359705650571

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.