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A Copula Based Method for the Classification of Fish Species

Author

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  • Raj Singh Dhawal

    (University of Northern British Columbia, Prince George, Canada)

  • Liang Chen

    (University of Northern British Columbia, Prince George, Canada)

Abstract

The proposed work develops a method for classification of the species of a fish given in an image, which is a sub-ordinate level classification problem. Fish image categorization is unique and challenging as the images of same fish species can show significant differences in the fish's attributes when taken in different conditions. The authors' approach analyses the local patches of images, cropped based on specific body parts, and hence keep comparison more specific to grab more finer details rather than comparing global postures. The authors have used Histogram of Oriented Gradients and colour histograms to create representative feature vectors; feature vectors are summarized using Copula theory. Their method is very simple yet they have matched the classification accuracy of other proposed complex work for such problems.

Suggested Citation

  • Raj Singh Dhawal & Liang Chen, 2017. "A Copula Based Method for the Classification of Fish Species," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 11(1), pages 29-45, January.
  • Handle: RePEc:igg:jcini0:v:11:y:2017:i:1:p:29-45
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