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Quality Inspection of Dented Capsule using Curve Fitting-based Image Segmentation

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2016, 21(12), pp.125-130
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Kwon Ki Hyeon 1 Hyung-Bong Lee 2

1강원대학교
2강릉원주대학교

Accredited

ABSTRACT

Automatic quality inspection by computer vision can be applied and give a solution to the pharmaceutical industry field. Pharmaceutical capsule can be easily affected by flaws like dents, cracks, holes, etc. In order to solve the quality inspection problem, it is required computationally efficient image processing technique like thresholding, boundary edge detection and segmentation and some automated systems are available but they are very expensive to use. In this paper, we have developed a dented capsule image processing technique using edge-based image segmentation, TLS(Total Least Squares) curve fitting technique and adopted low cost camera module for capsule image capturing. We have tested and evaluated the accuracy, training and testing time of the classification recognition algorithms like PCA(Principal Component Analysis), ICA(Independent Component Analysis) and SVM(Support Vector Machine) to show the performance. With the result, PCA, ICA has low accuracy, but SVM has good accuracy to use for classifying the dented capsule.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.