Search this article in Google Scholar


分類 国際会議
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)
表題 (title) {An Efficient Parts Counting Method based on Intensity Distribution Analysis for Industrial Vision Systems}
表題 (英文)
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) March
出版年 (year) 2018
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


[1-364]  Qiaochu Zhao, Ittetsu Taniguchi, Makoto Nakamura, and Takao 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. (Kunibiki Messe, Matsue, Japan)

@inproceedings{1_364,
    author = {Qiaochu Zhao and Ittetsu Taniguchi and Makoto Nakamura and Takao
    Onoye},
    author_e = {},
    editor = {},
    editor_e = {},
    title = {{An Efficient Parts Counting Method based on Intensity Distribution
    Analysis for Industrial Vision Systems}},
    title_e = {},
    booktitle = {The 21st Workshop on Synthesis And System Integration of Mixed
    Information techologies},
    booktitle_e = {},
    volume = {},
    number = {},
    pages = {},
    organization = {},
    publisher = {},
    publisher_e = {},
    address = {},
    month = {March},
    year = {2018},
    note = {Kunibiki Messe, Matsue, Japan},
    annote = {}
}

This site is maintained by Onoye Lab.

PMAN 2.5.5 - Paper MANagement system / (C) 2002-2008, Osamu Mizuno / All rights reserved.