JParticles

Image processing and analysing software

Introduction

This work deals with the basic concepts of image processing, the challenges set by the analysis of nuclear solid state detectors, and possible answers to these challenges. Cosmic rays are energetic particles originating from outer space. A frequently used technique to analyze these particles is ‘Solid State Nuclear Track Detection’ (SSNTD), also known as ‘Nuclear Track Analysis’. In the above mentioned technique small plastic plates are used, which are sensitive to heavy ions of all energies, and thus are able to detect the heavy ions, leaving tracks on such plates. These detectors cannot be read out on-orbit. They need to be returned to the ground for chemical processing and analysis.

Project goals and development

The goal of this work is to develop a complete system, which analyzes autonomously these tracks, and is prepared to deal with special cases, which may occur during the analyzing process.
A special image processing and analyzing software (JParticles) is under development, capable of recognizing some of these tracks, and handling composite (overlapping) and ‘drop shaped’ tracks. The software is based on the functionalities of the ImageJ image processing Java software.
The first version of the software was developed as a plugin for the ImageJ software, and used MATLAB codes directly from Java code (with remote calls). The second version of the software (which is currently under development) is a standalone application, using ImageJ as a library, and all the MATLAB algorithms and codes are translated to Java for better performance and portability.

Main features

The main features of the software are as follows:

  • Preprocessing dtector images (loading, filtering... etc.)
  • The preprocesing mechanism is parameterized and scriptable (ImageJ macros are used)
  • Object (BLOB) identification
  • Measurement of morphological parameters
  • Interactive view and GUI
  • Learning algorithms capable of classifying particle tracks
  • The BLOB identification is parameterized, learnable, testable
  • The software is capable of loading and saving project data (project management)