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Detecting visual plagiarism with perception hashing
KTH, School of Computer Science and Communication (CSC).
2015 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Classifying images and deciding algorithmically whether or not they are the same image is a complex problem in com-puter science. This report looks at using perceptual hashing in order to fingerprint images so that they may be matched to one and other.

The results shows that threshold match-ing images can be done with good accuracy, while a zero distance match is not reliable in most scenarios. The con-clusion is that a hybrid approach that uses a more inclu-sive perception algorithm to filter out candidates for a more thorough algorithm might be a good choice.

Place, publisher, year, edition, pages
2015.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-166771OAI: oai:DiVA.org:kth-166771DiVA: diva2:812148
Supervisors
Examiners
Available from: 2015-05-17 Created: 2015-05-16 Last updated: 2015-05-17Bibliographically approved

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fulltext(1016 kB)351 downloads
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File name FULLTEXT01.pdfFile size 1016 kBChecksum SHA-512
f5e5a3cd8a6a378a1eff7c15dd5fc668e16a289c05d56c4d5c8c77d7ecff6a554ec558f65d3947d72fae37cbbc046c98cf1c90e6afde2b05ca192cb0ffceec60
Type fulltextMimetype application/pdf

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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  • nn-NB
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More languages
Output format
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