Effective subpixel edge detection for LED probes

Chung Yen Su, Li An Yu, Nai Kuei Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

The market of light-emitting devices (LED) is growing dramatically over these years. To test the quality of LEDs, lots of LED probes are required. Therefore, it is important to develop an effective method to measure the angle (around 10 degrees) and the radius (15 μm ∼ 30 μm) of a produced LED probe. In this study, we propose a new subpixel edge detection for LED probes. The proposed method mainly consists of a coarse edge detection by Canny operators and a fine edge detection by a reconstructive method. In addition, an Otsu thresholding and a reflecting-point removal are included to reduce noise and increase accuracy. Compared to the previous methods, the proposed method can further reduce angle error up to 19.5% and the radius error up to 24.8%, respectively.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages379-382
Number of pages4
ISBN (Electronic)9781509018970
DOIs
Publication statusPublished - 2017 Feb 6
Event2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Budapest, Hungary
Duration: 2016 Oct 92016 Oct 12

Publication series

Name2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings

Other

Other2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016
Country/TerritoryHungary
CityBudapest
Period2016/10/092016/10/12

Keywords

  • Computer vision system
  • Image processing
  • LED probe
  • Subpixel edge detection

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Control and Optimization
  • Human-Computer Interaction

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