Adaptive thresholding by region of interest applied to quality control of gas electron multiplier foils

C. A. Rodriguez, R. M. Gutierrez, A. E. Jaramillo

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

Abstract

This paper presents a variation of the technique of adaptive thresholding, as a robust method for segmentation of holes in quality assurance of the Gas Electron Multiplier Foils by analyzing high-resolution images. The proposed thresholding is applied to the region of interest around the holes and offers an effective solution to lighting variations on the GEM-foil image. This technique together with some operations of mathematical morphology allows extracting contours of the holes for accurate quantification. The inner radius and roundness of the holes are used and proposed as a measure to characterize defects in GEM-foils. Techniques and methods described in this work were developed in Java programming language and implemented in the Software for Foils Analyzer (SOFA).

Original languageEnglish (US)
Title of host publication2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016
EditorsMiguel Altuve
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509037971
DOIs
StatePublished - Nov 14 2016
Event21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016 - Bucaramanga, Colombia
Duration: Aug 30 2016Sep 2 2016

Publication series

Name2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016

Conference

Conference21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016
CountryColombia
CityBucaramanga
Period8/30/169/2/16

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Artificial Intelligence

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    Rodriguez, C. A., Gutierrez, R. M., & Jaramillo, A. E. (2016). Adaptive thresholding by region of interest applied to quality control of gas electron multiplier foils. In M. Altuve (Ed.), 2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016 [7743297] (2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/STSIVA.2016.7743297