| Literature DB >> 34273617 |
Arvind Kumar1, Vivek Walia2, Srinivas Mogili1, Ching-Chou Fu3.
Abstract
An improved semi automatic technique for counting the tracks formed on LR-115 films with the advantages of simplicity and speed is reported. In this technique, a microscope with a Dino-Eye eyepiece camera is coupled to a PC equipped with a python compiler. After etching of the LR-115 film, 16 track images were taken to find the track density. The images generated were binarized before application of a Python algorithm. This process does not disfigure the original track and increase the spatial resolution. The batch process option in Jasc Paint Shop Pro was used to binarize the 16 images simultanously. The Python program automatically counts the total number of tracks formed on the 16 track images. This method was compared with manual counting and counting with the software program-Scion image to verify it. The results showed that the proposed method is reasonably good at counting the tracks. It is a faster and less time-consuming method, and will facilitate measurements of etched tracks in a variety of applications.Entities:
Keywords: Binarization; Counting; Etching; LR-115 films; Python; Solid state nuclear track detectors
Year: 2021 PMID: 34273617 DOI: 10.1016/j.apradiso.2021.109863
Source DB: PubMed Journal: Appl Radiat Isot ISSN: 0969-8043 Impact factor: 1.513