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dc.contributor.authorSatish Y.C.
dc.contributor.authorRudra B.
dc.identifier.citationAdvances in Intelligent Systems and Computing , Vol. 1177 , , p. 21 - 29en_US
dc.description.abstractImage processing in a surveillance video has been a challenging task in research and development for several years. Crimes in Automated Teller Machine (ATM) is common nowadays, in spite of having a surveillance camera inside an ATM as it is not fully integrated to detect crime/theft. On the other hand, we have many image processing algorithms that can help us to detect the covered faces, a person wearing a helmet and some other abnormal features. This paper proposes an alert system, by extracting various features like face-covering, helmet-wearing inside an ATM system to detect theft/crime that may happen. We cannot judge theft/crime as it may happen at any time but we can alert the authorized persons to monitor the video surveillance. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.en_US
dc.titleAtm theft investigation using convolutional neural networken_US
dc.typeConference Paperen_US
Appears in Collections:2. Conference Papers

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