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Pattern Classification and Recognition of Movement Behavior of Medaka (Oryzias Latipes) Using Decision Tree

  • Sengtai Lee
  • Jeehoon Kim
  • Jae-Yeon Baek
  • Man-Wi Han
  • Tae-Soo Chon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3614)

Abstract

Behavioral sequences of the medaka (Oryzias latipes) were continuously investigated through an automatic image recognition system in increasing temperature from 25°C to 35°C. The observation of behavior through the movement tracking program showed many patterns of the medaka. After much observation, behavioral patterns could be divided into basically 4 patterns: active- smooth, active-shaking, inactive-smooth, and inactive-shaking. The “smooth” and “shaking” patterns were shown as normal movement behavior, while the “smooth” pattern was more frequently observed in increasing temperature (35° C) than the “shaking” pattern. Each pattern was classified using a devised decision tree after the feature choice. It provides a natural way to incorporate prior knowledge from human experts in fish behavior and contains the information in a logical expression tree. The main focus of this study was to determine whether the decision tree could be useful in interpreting and classifying behavior patterns of the medaka.

Keywords

Decision Tree Fast Fourier Transform Pattern Classification Movement Track Movement Behavior 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Sengtai Lee
    • 1
  • Jeehoon Kim
    • 2
  • Jae-Yeon Baek
    • 2
  • Man-Wi Han
    • 2
  • Tae-Soo Chon
    • 3
  1. 1.School of Electrical EngineeringPusan National UniversityBusanKorea
  2. 2.Korea Minjok Leadership AcademyGangwon-doKorea
  3. 3.Division of Biological SciencesPusan National UniversityBusanKorea

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