Disclosed is a technique related to a railway disaster monitoring system for monitoring foreign substances on railways, which comprises: a camera; and an image processing device receiving a railroad image captured by the camera. The image processing device includes: a segmented image acquisition unit obtaining multiple segmented images, including rails, from the railway image received from the camera, and scaling the segmented images to obtain segmented image blocks of a predetermined size; and a segmented image determination unit having a first DNN discriminator trained with a deep learning neural network, and inputting the segmented image blocks into the first DNN discriminator to determine whether railways are normal railways having no foreign substances thereon. The segmented images can be used to quickly and easily discriminate a deep learning neural network even with fewer resources.

    카메라와, 상기 카메라에서 촬영한 철도 이미지를 입력받는 이미지 처리 장치를 포함하며, 철도 위의 이물질을 감시하는 철도 재난 감시 시스템에 관한 기술이 개시된다. 이미지 처리 장치는, 카메라로부터 입력받은 철도 이미지에서 레일을 포함하는 복수의 분할 이미지를 얻고, 분할 이미지를 스케일링하여 일정한 크기의 분할 이미지 블록을 구하는 분할 이미지 취득부와, 딥러닝 신경망으로 훈련시킨 제1 DNN 판별기를 구비하여, 분할 이미지 블록을 제1 DNN 판별기에 투입하여 철도 위에 이물질이 없는 정상상태의 철도인지 여부를 판단하는 분할 이미지 판단부를 포함한다. 분할 이미지를 사용하여 적은 자원으로도 딥러닝 신경망 판별을 빠르고 쉽게 할 수 있다.


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    Title :

    Railway Disaster Monitoring System


    Additional title:

    철도 재난 감시 시스템


    Contributors:

    Publication date :

    2023-06-01


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Korean


    Classification :

    IPC:    G06T Bilddatenverarbeitung oder Bilddatenerzeugung allgemein , IMAGE DATA PROCESSING OR GENERATION, IN GENERAL / B61L Leiten des Eisenbahnverkehrs , GUIDING RAILWAY TRAFFIC / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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