Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/149631
Title: Real-time edge detection and digital image processing system based on FPGA
Authors: Zhao, Junkai
Keywords: Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Zhao, J. (2021). Real-time edge detection and digital image processing system based on FPGA. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149631
Abstract: With the rapid development of science and technology, computers have been widely used in many fields. One of the most important applications is the processing of graphics and image information, that is, digital image processing. At present, there is a demand for digital image processing technology in many aspects such as agriculture and animal husbandry, forestry, environment, military, industry and medicine. However, due to the increase in the amount of transmitted data and the demand for real-time function, traditional digital image processing methods can no longer meet the demand. In this case, edge detection can be used to greatly reduce the amount of data, and eliminate information that is considered irrelevant or unimportant, and retain the most important structural attributes of the image. Therefore, in order to meet the above requirements, this project is dedicated to design a Real-Time Edge Detection and Digital Image Processing System based on FPGA. Firstly, this dissertation briefly introduces the development status and research background of imaging systems. Then it introduces the basic architecture of FPGA and the general framework of the system. Secondly, on the basis of in-depth analysis of the working principle of all functional modules to be used in the system, this dissertation completes the system hardware design. And it uses FPGA as the processor to realize image processing. In this part, it mainly deals with the configuration and connections for each module. Then, according to the actual application requirements, the edge detection algorithm and median filter are studied. Finally, the processed image data is converted into the video signal and displayed on the screen in real time. Last but not least, by observing and testing, the digital image processing system still has some defects. So, the optimization method and improvement direction are put forward.
URI: https://hdl.handle.net/10356/149631
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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