2D Feature Space for Snow Particle Classification into Snowflake and Graupel

DOI Web Site 被引用文献1件 参考文献22件 オープンアクセス
  • NURZYNSKA Karolina
    School of Electrical and Computer Engineering, Institute of Science and Engineering, Kanazawa University
  • KUBO Mamoru
    School of Electrical and Computer Engineering, Institute of Science and Engineering, Kanazawa University
  • MURAMOTO Ken-ichiro
    School of Electrical and Computer Engineering, Institute of Science and Engineering, Kanazawa University

書誌事項

公開日
2010
DOI
  • 10.1587/transinf.e93.d.3344
公開者
一般社団法人 電子情報通信学会

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説明

This study presents three image processing systems for snow particle classification into snowflake and graupel. All of them are based on feature classification, yet as a novelty in all cases multiple features are exploited. Additionally, each of them is characterized by a different data flow. In order to compare the performances, we not only consider various features, but also suggest different classifiers. The best achieved results are for the snowflake discrimination method applied before statistical classifier, as the correct classification ratio in this case reaches 94%. In other cases the best results are around 88%.

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