Recognition and classification of the cosmic-ray events in images captured by CMOS/CCD cameras

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21670%2F19%3A00373949" target="_blank" >RIV/68407700:21670/19:00373949 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21670/21:00373878

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Recognition and classification of the cosmic-ray events in images captured by CMOS/CCD cameras

Popis výsledku v původním jazyce

Muons and other ionizing radiation produced by cosmic rays and radiative decays affect CMOS/CCD sensor. When particles colliding with sensors atoms cause specific kind of noise on images recorded by cameras. We present a concept and preliminary implementation of method for recognizing those events and algorithms for image processing and their classification by machine learning. Our method consists of analyzing the shape of traces present in images recorded by a camera sensor and metadata related to an image like camera model, GPS location of camera, vertical and horizontal orientation of a camera sensor, timestamp of image acquisition, and other events recognized near-by sensors. The so created feature vectors are classified as either a muon-like event, an electron-like event or the other event, possibly noise. For muon-like events our method estimates azimuth of a muon track. Source of the data is database of CREDO (Cosmic-Ray Extremely Distributed Observatory) project and ESO (European Southern Observatory) archives. The telescope dark frames from ESO are analysed. CREDO project collected so far over 2 millions images of events from many kinds of cameralike: smartphones camera, laptop webcams and Internet of Things cameras localised around the globe.

Název v anglickém jazyce

Recognition and classification of the cosmic-ray events in images captured by CMOS/CCD cameras

Popis výsledku anglicky

Muons and other ionizing radiation produced by cosmic rays and radiative decays affect CMOS/CCD sensor. When particles colliding with sensors atoms cause specific kind of noise on images recorded by cameras. We present a concept and preliminary implementation of method for recognizing those events and algorithms for image processing and their classification by machine learning. Our method consists of analyzing the shape of traces present in images recorded by a camera sensor and metadata related to an image like camera model, GPS location of camera, vertical and horizontal orientation of a camera sensor, timestamp of image acquisition, and other events recognized near-by sensors. The so created feature vectors are classified as either a muon-like event, an electron-like event or the other event, possibly noise. For muon-like events our method estimates azimuth of a muon track. Source of the data is database of CREDO (Cosmic-Ray Extremely Distributed Observatory) project and ESO (European Southern Observatory) archives. The telescope dark frames from ESO are analysed. CREDO project collected so far over 2 millions images of events from many kinds of cameralike: smartphones camera, laptop webcams and Internet of Things cameras localised around the globe.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10308 - Astronomy (including astrophysics,space science)

Projekt

<a href="/cs/project/EF16_019%2F0000766" target="_blank" >EF16_019/0000766: Inženýrské aplikace fyziky mikrosvěta</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

36th International Cosmic Ray Conference

ISBN

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ISSN

1824-8039

e-ISSN

1824-8039

Počet stran výsledku

8

Strana od-do

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Název nakladatele

Proceedings of Science

Místo vydání

Trieste

Místo konání akce

Madison, Wisconsin

Datum konání akce

24. 7. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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