Real-Time Image and Video Processing Applications Using Raspberry Pi

Yıldırım, Merve; Karaduman, O.; Kürüm, Hasan

doi:10.1109/oncon56984.2022.10127034

2022 IEEE 1st Industrial Electronics Society Annual on-Line Conference (ONCON) 2022

DOI: 10.1109/oncon56984.2022.10127034

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Real-Time Image and Video Processing Applications Using Raspberry Pi

Merve Yıldırım

O. Karaduman

Hasan Kürüm

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2023

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Cited by 1 publication

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Power Requirements Evaluation of Embedded Devices for Real-Time Video Line Detection

Suder,

Podbucki,

Marciniak

2023

Energies

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In this paper, the comparison of the power requirements during real-time processing of video sequences in embedded systems was investigated. During the experimental tests, four modules were tested: Raspberry Pi 4B, NVIDIA Jetson Nano, NVIDIA Jetson Xavier AGX, and NVIDIA Jetson Orin AGX. The processing speed and energy consumption have been checked, depending on input frame size resolution and the particular power mode. Two vision algorithms for detecting lines located in airport areas were tested. The results show that the power modes of the NVIDIA Jetson modules have sufficient computing resources to effectively detect lines based on the camera image, such as Jetson Xavier in mode MAXN or Jetson Orin in mode MAXN, with a resolution of 1920 × 1080 pixels and a power consumption of about 19 W for 24 FPS for both algorithms tested.

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Power Requirements Evaluation of Embedded Devices for Real-Time Video Line Detection

Suder,

Podbucki,

Marciniak

2023

Energies

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Real-Time Image and Video Processing Applications Using Raspberry Pi

Cited by 1 publication

References 24 publications

Power Requirements Evaluation of Embedded Devices for Real-Time Video Line Detection

Power Requirements Evaluation of Embedded Devices for Real-Time Video Line Detection

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