NEARBY Platform: Algorithm for Automated Asteroids Detection in Astronomical Images

T. Stefanut, V. Bâcu, C. Nandra, Denisa Balasz, D. Gorgan, Ovidiu Vaduvescu
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引用次数: 4

Abstract

In the past two decades an increasing interest in discovering Near Earth Objects has been noted in the astronomical community. Dedicated surveys have been operated for data acquisition and processing, resulting in the present discovery of over 18.000 objects that are closer than 30 million miles of Earth. Nevertheless, recent events have shown that there still are many undiscovered asteroids that can be on collision course to Earth. This article presents an original NEO detection algorithm developed in the NEARBY research object, that has been integrated into an automated MOPS processing pipeline aimed at identifying moving space objects based on the blink method. Proposed solution can be considered an approach of Big Data processing and analysis, implementing visual analytics techniques for rapid human data validation.
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near平台:天文图像中自动小行星探测算法
在过去的二十年里,天文学界对发现近地天体的兴趣日益浓厚。专门的调查已经用于数据采集和处理,导致目前发现了18000多个离地球近3000万英里的物体。然而,最近的事件表明,仍有许多未被发现的小行星可能会撞向地球。本文提出了一种基于near研究对象开发的新颖近地天体探测算法,并将其集成到基于眨眼法的MOPS自动化处理流水线中,用于识别空间运动物体。提出的解决方案可以被认为是大数据处理和分析的一种方法,实现了快速人工数据验证的可视化分析技术。
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