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A novel, smart and fast searching method for star pattern recognition using star magnitudes

机译:一种新颖,智能,快速的利用星等识别星型的方法

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The key performances of the star pattern recognition algorithms are the identification efficiency and the time consumed. In the past decades, much effort has been made, and lots of them are made out. To reduce the computations database search and star features extraction time and increasing the accuracy of star pattern recognition algorithm a novel, smart and fast star identification algorithm by using star magnitudes is proposed. The simulation results based on the Desktop Universes images show that the proposed star identification and database search algorithm can achieve both high accuracy and fast recognition. The database search and star features extraction time is O(n). In addition to, since the quality of star images play an important role in improving accuracy of star pattern recognition algorithm, therefore for image pre-processing we propose a fuzzy edge detection technique. This method highly affects noise cancellation, star features extraction, database production and matching algorithm.
机译:星型识别算法的关键性能是识别效率和耗时。在过去的几十年中,已经付出了很多努力,并且做出了很多努力。为了减少数据库搜索和星特征提取的时间,提高星型识别算法的准确性,提出了一种新颖,智能,快速的星大小识别算法。基于Desktop Universes图像的仿真结果表明,所提出的恒星识别和数据库搜索算法可以实现高精度和快速识别。数据库搜索和星形特征提取时间为O(n)。此外,由于星形图像的质量在提高星形模式识别算法的准确性方面起着重要作用,因此对于图像预处理,我们提出了一种模糊边缘检测技术。该方法极大地影响噪声消除,星特征提取,数据库生成和匹配算法。

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