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Twist-State Classifier for Floating Marine Biomass Based on Physical Simulation

  • Jun Ogawa
  • Hiroyuki Iizuka
  • Masahito Yamamoto
  • Masashi Furukawa
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 302)

Abstract

This paper describes new approaches for classifying twist of seaweeds. There are no evaluation measures of the twist formation of complicated objects quantitatively because the definition of a qualitative twist is a difficult problem. The twist of seaweeds is one of these problems. In this paper, we propose three factors (physical, geometric, and time factor of twist) for characterizing the twist state, and we develop the twist-state classifier based on these factors. Additionally, the analysis experiment verifies how the classifier shows the classification accuracy of twist state.

Keywords

Twist Physical simulation Feature quantity Classification 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jun Ogawa
    • 1
  • Hiroyuki Iizuka
    • 1
  • Masahito Yamamoto
    • 1
  • Masashi Furukawa
    • 2
  1. 1.Hokkaido UniversitySapporoJapan
  2. 2.Hokkaido Information UniversityEbetsuJapan

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