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Noise-added texture analysis
Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
2017 (English)In: PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2016 / [ed] Beltrán-Castañón, Cesar, Nyström, Ingela, Famili, Fazel, Springer, 2017, p. 93-100Conference paper, Published paper (Refereed)
Abstract [en]

Noise is unwanted signal that causes a major problem for the task of image classification and retrieval. However, this paper reports that adding noise to texture at certain levels can improve classification performance without training data. The proposed method was tested with images of different texture categories degraded with various noise types: Gaussian (additive), salt-and-pepper (impulsive), and speckle (multiplicative). Experimental results suggest that the inclusion of noise can be useful for extracting texture features for image retrieval.

Place, publisher, year, edition, pages
Springer, 2017. p. 93-100
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 10125
Keywords [en]
Texture; Noise; Geostatistics; Spectral distortion; Image retrieval 
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-133874DOI: 10.1007/978-3-319-52277-7_12ISI: 000418399200012ISBN: 978-3-319-52276-0 (print)ISBN: 978-3-319-52277-7 (electronic)OAI: oai:DiVA.org:liu-133874DiVA, id: diva2:1064798
Conference
21st Iberoamerican Congress, CIARP 2016, Lima, Peru, November 8–11, 2016
Available from: 2017-01-13 Created: 2017-01-13 Last updated: 2018-02-12

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Pham, Tuan
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Total: 103 hits
CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf