Detection of variable stars by time series analysis of the overlapping areas from large-scale astronomical image data sets
| Project/Area Number |
15K12068
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Perceptual information processing
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| Research Institution | Chukyo University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
高妻 真次郎 中京大学, 国際教養学部, 准教授 (60584183)
道満 恵介 中京大学, 工学部, 講師 (90645748)
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2017: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2015: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | 画像処理 / 天体画像 / パターン認識 / 画像 |
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| Outline of Final Research Achievements |
In this research project, as one of astronomical data analysis support technologies, we developed a framework for automatic detection of variable stars by time series analysis from large-scale astronomical image data sets, and also developed fundamental image processing / pattern recognition techniques for this framework. We focused on overlapping areas between celestial images. Therefore, we developed a method to align these images. Variable star detection based on the method of detecting the change in the brightness of the star in the detected overlap region was carried out. For the former, we developed a high-speed overlap region detection method and made large scale experiments possible. In the latter, accuracy was improved by determining the adaptive variable star detecting condition by the brightness of the fixed star. Moreover, to improve the detection precision of the fixed star, we developed a method of approximating the star region by Gaussian distribution.
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Report
(4 results)
Research Products
(3 results)
