Convolution based hybrid image processing technique for microscopic images of etch-pits in Nuclear Track Detectors

TL;DR

This paper introduces a convolution-based hybrid image processing method for analyzing etch-pit images in Nuclear Track Detectors, improving identification and counting accuracy across different NTD types and etch-pit shapes.

Contribution

The paper presents a novel convolution-based technique specifically designed for analyzing etch-pits in NTDs, demonstrating its effectiveness on various detector types and pit geometries.

Findings

Effective identification of etch-pits in NTDs

Accurate counting of etch-pits across different shapes

Promising results on multiple NTD types

Abstract

A novel image processing technique based on convolution is developed for analyzing the etch-pit images in Nuclear Track Detectors (NTDs). The outcomes of the application of the proposed method on the different types of NTDs (e.g., CR-39, PET) containing etch-pit openings of different sizes and shapes (circular and elliptical) is presented. Promising results have been obtained for both identifying and counting the etch-pits in NTDs.