Object recognition for control panels on machine tools with HOG and Bag of Keypoints

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Other Title
  • HOG と Bag of Keypoints を用いた工作機械用制御盤内における物体認識

Description

Currently, the components in the control panel for machine tools, electrical wiring connections are called harnesses performed manually. Therefore, it is required by a machine to automate its work. The purpose of this study is performing by image recognition of these two things. First, detecting the pre-installed screw with components in order to wire harness automatically. Second, scanning the connected harness after installing the harness. In this study, we use a technique called generic object recognition which learns and classifies the image feature by means of machine learning. We use HOG (Histograms of Oriented Gradients) and Bag of Keypoints as a method of calculation for the feature, AdaBoost and SVM (Support Vector Machine) as a method of machine learning. In this paper, we show the detection rate of screws and harnesses using the method described above.

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Details 詳細情報について

  • CRID
    1390001205185467648
  • NII Article ID
    130002096893
  • DOI
    10.3156/jsoft.24.909
  • ISSN
    18817203
    13477986
  • Text Lang
    ja
  • Article Type
    journal article
  • Data Source
    • JaLC
    • Crossref
    • CiNii Articles
    • KAKEN
  • Abstract License Flag
    Disallowed

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