尾上研究室 研究業績一覧: Q. Zhao, I. Taniguchi, M. Nakamura, and T. Onoye, {An Efficient Parts Counting Method Based on Intensity Distribution Analysis for Industrial Vision Systems}, March 2018.
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Q. Zhao, I. Taniguchi, M. Nakamura, and T. Onoye, "{An Efficient Parts Counting Method Based on Intensity Distribution Analysis for Industrial Vision Systems}," In The 21st Workshop on Synthesis And System Integration of Mixed Information techologies, March 2018.
ID 854
分類 国際会議
タグ
表題 (title) {An Efficient Parts Counting Method Based on Intensity Distribution Analysis for Industrial Vision Systems}
表題 (英文)
著者名 (author) Qiaochu Zhao,Ittetsu Taniguchi,Makoto Nakamura,Takao Onoye
英文著者名 (author)
編者名 (editor)
編者名 (英文)
キー (key)
書籍・会議録表題 (booktitle) The 21st Workshop on Synthesis And System Integration of Mixed Information techologies
書籍・会議録表題(英文)
巻数 (volume)
号数 (number)
ページ範囲 (pages)
組織名 (organization)
出版元 (publisher)
出版元 (英文)
出版社住所 (address)
刊行月 (month) 3
出版年 (year) 2018
採択率 (acceptance)
URL
付加情報 (note) Kunibiki Messe, Matsue, Japan
注釈 (annote)
内容梗概 (abstract) In this paper, we proposed an efficient parts counting method based on intensity distribution analysis for industrial vision system. Counting productions, as a preliminary operation in assemble line, is essential for calculating many industrial index such as deficiency rate. Conventional approach for counting problem is based on template matching, which we consider it as both stiff and time-consuming. In the proposed approach, counting problem is converted into an equivalent classification problem, in which a trained classifier is used to classify whether a specific line segment region belongs to parts or not. While parts flow through this line segment, number of the flowed parts can be effectively counted according to the interlace of different classified results. Experiments revealed that the proposed method superiors conventional template-matching method by being capable of counting with significant improvement of speed as well as with higher accuracy and stronger robustness. We also considered the proposed method can be readily extended to data with similar properties.
論文電子ファイル 2.pdf (application/pdf) [一般閲覧可]
BiBTeXエントリ
@inproceedings{id854,
         title = {{An Efficient Parts Counting Method based on Intensity Distribution Analysis for Industrial Vision Systems}},
        author = {Qiaochu Zhao and Ittetsu Taniguchi and Makoto Nakamura and Takao Onoye},
     booktitle = {The 21st Workshop on Synthesis And System Integration of Mixed Information techologies},
         month = {3},
          year = {2018},
          note = {Kunibiki Messe, Matsue, Japan},
}
  

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