• Title/Summary/Keyword: AI 영상인식

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Design and Implementation of a Hardware Accelerator for Marine Object Detection based on a Binary Segmentation Algorithm for Ship Safety Navigation (선박안전 운항을 위한 이진 분할 알고리즘 기반 해상 객체 검출 하드웨어 가속기 설계 및 구현)

  • Lee, Hyo-Chan;Song, Hyun-hak;Lee, Sung-ju;Jeon, Ho-seok;Kim, Hyo-Sung;Im, Tae-ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.10
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    • pp.1331-1340
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    • 2020
  • Object detection in maritime means that the captain detects floating objects that has a risk of colliding with the ship using the computer automatically and as accurately as human eyes. In conventional ships, the presence and distance of objects are determined through radar waves. However, it cannot identify the shape and type. In contrast, with the development of AI, cameras help accurately identify obstacles on the sea route with excellent performance in detecting or recognizing objects. The computer must calculate high-volume pixels to analyze digital images. However, the CPU is specialized for sequential processing; the processing speed is very slow, and smooth service support or security is not guaranteed. Accordingly, this study developed maritime object detection software and implemented it with FPGA to accelerate the processing of large-scale computations. Additionally, the system implementation was improved through embedded boards and FPGA interface, achieving 30 times faster performance than the existing algorithm and a three-times faster entire system.