An automatic method for segmentation of fission tracks in epidote crystal photomicrographs

Manual identification of fission tracks has practical problems, such as variation due to observer-observation efficiency. An automatic processing method that could identify fission tracks in a photomicrograph could solve this problem and improve the speed of track counting. However, separation of nontrivial images is one of the most difficult tasks in image processing. Several commercial and free softwares are available, but these softwares are meant to be used in specific images. In this paper, an automatic method based on starlet wavelets is presented in order to separate fission tracks in mineral photomicrographs. Automatization is obtained by Matthews correlation coefficient, and results are evaluated by precision, recall and accuracy. This technique is an improvement of a method aimed at segmentation of scanning electron microscopy images. This method is applied in photomicrographs of epidote phenocrystals, in which accuracy higher than 89% was obtained in ∗Corresponding author. Phones: +55(18)3229-5776 / +55(18)3229-5775. Email addresses: [email protected] (Alexandre Fioravante de Siqueira), [email protected] (Wagner Massayuki Nakasuga), [email protected] (Aylton Pagamisse), [email protected] (Carlos Alberto Tello Saenz), [email protected] (Aldo Eloizo Job) Published in Computers & Geosciences (August 2014). The final publication is available at http://dx.doi.org/10.1016/j.cageo.2014.04.008. Preprint submitted to Computers & Geosciences April 8, 2014 ar X iv :1 60 2. 03 99 5v 1 [ cs .C V ] 1 2 Fe b 20 16 fission track segmentation, even for difficult images. Algorithms corresponding to the proposed method are available for download. Using the method presented here, an user could easily determine fission tracks in photomicrographs of mineral samples.