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

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概要

• 論文の詳細を見る

• 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%.

• （社）電子情報通信学会の論文
• 2010-12-01

著者

• Kubo Mamoru

  School Of Electrical And Computer Engineering Institute Of Science And Engineering Kanazawa Universi

• NURZYNSKA Karolina

  School of Electrical and Computer Engineering, Institute of Science and Engineering, Kanazawa Univer

• MURAMOTO Ken-ichiro

  School of Electrical and Computer Engineering, Institute of Science and Engineering, Kanazawa Univer

• Muramoto Ken-ichiro

  School Of Electrical And Computer Engineering Institute Of Science And Engineering Kanazawa Universi

• Nurzynska Karolina

  School Of Electrical And Computer Engineering Institute Of Science And Engineering Kanazawa Universi

関連論文

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

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