Comparison of Texture Recognition Algorithms

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Abstract

Texture plays an important role in human everyday life. Through textures humans can distinguish different types of objects. Texture recognition has important application in fields like remote sensing, industrial surface inspection and biomedical image analysis. Vision is the pivotal way in which textures are recognised. Most existing texture identification algorithms use greyscale images to detect textures. In this paper a texture recognition approach based on the use of Gabor filters and Local binary patterns is used in conjunction with an SVM. An existing texture identification dataset is used to perform comparative analysis and results demonstrate that local binary pattern approach has superior performance.
Original languageEnglish
Pages209
Number of pages216
Publication statusPublished - 29 Aug 2018
EventIrish Machine Vision and Image Processing Conference - Belfast, United Kingdom
Duration: 29 Aug 201831 Aug 2018

Conference

ConferenceIrish Machine Vision and Image Processing Conference
Abbreviated titleIMVIP
CountryUnited Kingdom
Period29/08/1831/08/18

Keywords

  • Texture recognition
  • Gabor filters
  • Support Vector Machines
  • Local binary pattern

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    John Bensam, C. S., Coleman, S., Kerr, D., Gardiner, B., & Wu, C. (2018). Comparison of Texture Recognition Algorithms. 209. Poster session presented at Irish Machine Vision and Image Processing Conference, United Kingdom.