Automatic evaluation of solid state track detectors by artificial vision

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.

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► Low-contrast images of scanning electron microscope are processed directly.
► Tracks of collisions are detected automatically without cumbersome adjustments.
► The statistics of a package of images can be obtained by a batch processing.
► The processing time is quite low and the outcomes highly satisfactory.