Title Details: | |
Laboratory Exercise: Implementing an image algorithm on Nvidia Tegra X1 GPU SoC |
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Authors: |
Dasygenis, Minas Soudris, Dimitrios |
Description: | |
Abstract: |
In recent years, the continually advancing technological developments have led to the creation of more complex and computationally intensive image processing algorithms. Many of these algorithms have been adopted in today’s embedded systems targeting various applications such as the automotive industry, 3D navigation, surveillance etc. However, in real-time embedded systems, where latency and power play a crucial role, software-oriented implementations for general-purpose CPUs may not offer satisfactory solutions. The purposes of this project are to design an image processing system for embedded applications, develop it on a System-on-Chip (SoC) platform and evaluate the developed System. The Harris Corner Detector algorithm was chosen to be implemented in a real-time system that captures the input image from a camera. The main goal of the project is to implement the Harris-Corner algorithm on a Tegra X1 GPU SoC. Optimizations of the algorithm for increased speed will also be studied.
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Linguistic Editors: |
Kagiadaki, Sofia |
Technical Editors: |
Dasygenis, Minas |
Graphic Editors: |
Dasygenis, Minas |
Type: |
Chapter |
Creation Date: | 28-08-2024 |
Item Details: | |
License: |
Attribution - NonCommercial - ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
Handle | http://hdl.handle.net/11419/13882 |
Bibliographic Reference: | Dasygenis, M., & Soudris, D. (2024). Laboratory Exercise: Implementing an image algorithm on Nvidia Tegra X1 GPU SoC [Chapter]. In Dasygenis, M., & Soudris, D. 2024. Internet of Things Computing [Undergraduate textbook]. Kallipos, Open Academic Editions. https://hdl.handle.net/11419/13882 |
Language: |
Greek |
Is Part of: |
Internet of Things Computing |
Publication Origin: |
Kallipos, Open Academic Editions |