Automatic evaluation of solid state track detectors by artificial vision

  • Authors:

  • Armando Segovia;Mayra GarduñO;Miguel BalcáZar;LuíS Ledezma

  • Affiliations:

  • Instituto Nacional de Investigaciones Nucleares, Carretera México-Toluca s/n, La Marquesa, Ocoyoacac, Estado de México, CP 52750, Mexico and Instituto Tecnológico de Toluca, Av. Ins ...;Instituto Tecnológico de Toluca, Av. Inst. Tec. s/n, Metepec, Edo. de México, CP 52140, Mexico;Instituto Nacional de Investigaciones Nucleares, Carretera México-Toluca s/n, La Marquesa, Ocoyoacac, Estado de México, CP 52750, Mexico;Instituto Nacional de Investigaciones Nucleares, Carretera México-Toluca s/n, La Marquesa, Ocoyoacac, Estado de México, CP 52750, Mexico

  • Venue:
  • Computers and Electrical Engineering
  • Year:
  • 2013

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Abstract

Materials CR-39 and Makrofol have a wide range of applications in daily life, but both have an alternative application: the measurement of neutron radiation. To do this, the traces created by particles impacting the detecting material must be evaluated; this task is highly difficult and complex because particles are microscopic. To automatically evaluate tracks produced by light (alphas) and heavy ions (fission fragments) colliding perpendicularly in CR 39 Solid State Nuclear Track Detectors, a method based on artificial vision and pattern recognition techniques has been designed. With this method, detectors are evaluated by determining circumferential tracks, and digital images of scanning electron and optical microscopes are processed by using the Hough Transform; the resulting circumference parameters are refined using the Max-Min clustering algorithm. This methodology greatly accelerates the analysis of tracks in these detectors.