J. Space Weather Space Clim.
Volume 6, 2016
Statistical Challenges in Solar Information Processing
|Number of page(s)
|08 March 2016
An evolutionary computation based algorithm for calculating solar differential rotation by automatic tracking of coronal bright points
Computational Intelligence Group of CTS/UNINOVA, 2829-516
Monte de Caparica, Portugal
2 Department of Computer and Electrical Engineering, FCT/NOVA University of Lisbon, 2829-516 Monte de Caparica, Portugal
3 Slovak Central Observatory, Hurbanovo, Slovak Republic
* Corresponding author: email@example.com
Accepted: 2 February 2016
Developing specialized software tools is essential to support studies of solar activity evolution. With new space missions such as Solar Dynamics Observatory (SDO), solar images are being produced in unprecedented volumes. To capitalize on that huge data availability, the scientific community needs a new generation of software tools for automatic and efficient data processing. In this paper a prototype of a modular framework for solar feature detection, characterization, and tracking is presented. To develop an efficient system capable of automatic solar feature tracking and measuring, a hybrid approach combining specialized image processing, evolutionary optimization, and soft computing algorithms is being followed. The specialized hybrid algorithm for tracking solar features allows automatic feature tracking while gathering characterization details about the tracked features. The hybrid algorithm takes advantages of the snake model, a specialized image processing algorithm widely used in applications such as boundary delineation, image segmentation, and object tracking. Further, it exploits the flexibility and efficiency of Particle Swarm Optimization (PSO), a stochastic population based optimization algorithm. PSO has been used successfully in a wide range of applications including combinatorial optimization, control, clustering, robotics, scheduling, and image processing and video analysis applications. The proposed tool, denoted PSO-Snake model, was already successfully tested in other works for tracking sunspots and coronal bright points. In this work, we discuss the application of the PSO-Snake algorithm for calculating the sidereal rotational angular velocity of the solar corona. To validate the results we compare them with published manual results performed by an expert.
Key words: Sun / Helioinformatics / Corona / Solar image processing / Machine learning
© E. Shahamatnia et al., Published by EDP Sciences 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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