Improvement of overlapping nuclear track densitometry

Area of Science:

• Nuclear Physics
• Materials Science
• Image Processing

Background:

• Solid-state nuclear track detectors (SSNTDs), like CR-39, are crucial for detecting charged particles.
• Manual counting of high-density tracks in SSNTDs is labor-intensive and prone to errors.
• Accurate track densitometry is essential for quantitative analysis in various scientific fields.

Purpose of the Study:

• To develop an automated system for accurate recognition and measurement of etched nuclear tracks in SSNTDs.
• To evaluate the performance of the KTTMS2 software using the Canny edge detection method for nuclear track densitometry.
• To improve the accuracy of track counting, especially in high-density and overlapping track scenarios.

Main Methods:

• Development of KTTMS2, a C++ based automated computer program with a user-friendly interface.
• Application of image processing techniques, specifically edge detection methods, to analyze images of etched tracks on CR-39 detectors.
• Utilizing the Canny edge detection algorithm for precise identification and measurement of nuclear tracks.

Main Results:

• The KTTMS2 system achieved 95% efficiency in detecting nuclear tracks, classifying the remaining 5% as background noise.
• The Canny edge detection method proved to be the most accurate technique for nuclear track densitometry.
• Error percentage in track counting was reduced from 7.63% to 3.23% for high-density tracks by accounting for overlapping tracks.

Conclusions:

• The automated KTTMS2 system significantly enhances the accuracy and efficiency of nuclear track analysis in SSNTDs.
• The Canny edge detection method is highly effective for precise densitometry, particularly with overlapping tracks.
• This automated approach offers a reliable solution for quantitative analysis in fields utilizing plastic nuclear track detectors.