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Improved Defect Classification of Printed Circuit Board Using SVM

  • Yuji Iwahori
  • Deepak Kumar
  • Takuya Nakagawa
  • M. K. Bhuyan
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 16)

Abstract

This paper proposes an analytical approach to make correct recognition between the true defect and the pseudo defect with visual inspection of the electronic board. Some classification approaches have already been proposed for the limited kinds of defects but there have been incorrect recognitions for the defects which is difficult to handle with the visual inspection. This paper proposes the approach to reduce the incorrect recognition for the defects using Support Vector Machine. Real electronic board image data are tested and evaluated with the proposed approach. It is shown that the proposed approach gives efficient classification with some new features with a proper analysis on histogram of image according to the proposed evaluation criteria for the performance.

Keywords

Support Vector Machine Defect Image Average Gray Level True Defect Incorrect Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yuji Iwahori
    • 1
  • Deepak Kumar
    • 2
  • Takuya Nakagawa
    • 1
  • M. K. Bhuyan
    • 2
  1. 1.Dept. of Computer ScienceChubu UniversityKasugaiJapan
  2. 2.Indian Institute of TechnologyGuwahatiIndia

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