Frog Identification System Based on Local Means K-Nearest Neighbors with Fuzzy Distance Weighting

  • Haryati Jaafar
  • Dzati Athiar Ramli
  • Bakhtiar Affendi Rosdi
  • Shahriza Shahrudin
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 291)

Abstract

Frog identification based on the vocalization becomes important for biological research and environmental monitoring. As a result, different types of feature extractions and classifiers have been employed. Yet, the k-nearest neighbor (kNN) is one of the popular classifiers and has been applied in various applications. This paper proposes an improvement of kNN in order to evaluate the accuracy of frog sound identification. The recorded sounds of 12 frog species obtained in Malaysia forest have been segmented using short time energy and short time average zero crossing rate while the features are extracted by mel frequency cepstrum coefficient. Finally, a proposed classifier based on local means kNN and fuzzy distance weighting have been employed to identify the frog species. Comparison of the system performances based on kNN, local means kNN and the proposed classifier i.e. fuzzy kNN with manual segmentation and automatic segmentation is evaluated. The results show the proposed classifier outperforms the baseline classifier with accuracy of 94.67 % and 98.33 % for manual and automatic segmentation, respectively.

Keywords

Frog identification kNN Local means KNN Fuzzy kNN Distance weighting 

Notes

Acknowledgments

The authors would like to thank the financial support provided by Universiti Sains Malaysia Short Term Grant, 304/PELECT/60311048, Research University Grant 814161 and Research University Grant 814098 for this project.

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Copyright information

© Springer Science+Business Media Singapore 2014

Authors and Affiliations

  • Haryati Jaafar
    • 1
  • Dzati Athiar Ramli
    • 1
  • Bakhtiar Affendi Rosdi
    • 1
  • Shahriza Shahrudin
    • 2
  1. 1.School of Electrical and Electronic EngineeringUSM Engineering CampusNibong TebalMalaysia
  2. 2.School of Pharmacy SciencesUSMMindenMalaysia

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