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An Improved Asterias Amurensis Recognition Method Based on Morphological Characteristics Analysis Techniques

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2012, 17(10), pp.61-69
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

신현덕 1 전영철 2

1서울여자대학교
2관동대학교

Accredited

ABSTRACT

The population of highly prolific, predatory Asterias amurensis is growing sharply from year to year along the coastline of Korea, a nation surrounded by water on three sides. To make matters worse, the fact that Asterias amurensis devours living fish and shellfish has caused a heavy loss for fishermen involved in the aquaculture industry. What it all boils down to is the significance of technologies allowing one to recognize Asterias amurensis individuals using underwater images for the purpose of exterminating Asterias amurensis or identifying a change in the population of Asterias amurensis or the migration route of Asterias amurensis. An improved Asterias amurensis recognition method based on the morphological characteristics of Asterias amurensis was proposed in this paper. The proposed recognition method aimed at cases marked by the lack of extraction information on concaveness and convexity, which are the morphological characteristics of Asterias amurensis. Extracting all the characteristics of Asterias amurensis from images taken underwater is very difficult. In this respect, the proposed recognition is effective in terms of recognizing individuals in a diversity of Asterias amurensis images. As a result of the experiment, Our proposed method has achieved superior performance with 92.5% than other method.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.