Image processing for transmission line extraction and detection

This dissertation presents the image processing for transmission line extraction and detection. It includes the procedure to realize the size measurement of the transmission line on PCB to assist the electromagnetic analysis. The project is developed with python and opencv comprising three par...

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Main Author: Zheng, Yu
Other Authors: Tan Eng Leong
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2022
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Online Access:https://hdl.handle.net/10356/161262
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1612622022-08-24T01:20:33Z Image processing for transmission line extraction and detection Zheng, Yu Tan Eng Leong School of Electrical and Electronic Engineering EELTan@ntu.edu.sg Engineering::Electrical and electronic engineering This dissertation presents the image processing for transmission line extraction and detection. It includes the procedure to realize the size measurement of the transmission line on PCB to assist the electromagnetic analysis. The project is developed with python and opencv comprising three parts, which are board extraction, transmission line detection and size measurement. The whole process involves the color model conversion (from RGB to HSV, RGB to grayscale), image smoothing (bilateral filtering), thresholding (OTSU adaptive threshold), image enhancement (morphological operation), contour findings, edge detection (Canny edge) and segmentation measurement. Through a combination of those methods in each step, we finally manage to extract the board from the background, detect all the transmission lines and measure their size. The size is measured in pixels rather than the actual length. Master of Science (Communications Engineering) 2022-08-24T01:20:33Z 2022-08-24T01:20:33Z 2022 Thesis-Master by Coursework Zheng, Y. (2022). Image processing for transmission line extraction and detection. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/161262 https://hdl.handle.net/10356/161262 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Zheng, Yu
Image processing for transmission line extraction and detection
description This dissertation presents the image processing for transmission line extraction and detection. It includes the procedure to realize the size measurement of the transmission line on PCB to assist the electromagnetic analysis. The project is developed with python and opencv comprising three parts, which are board extraction, transmission line detection and size measurement. The whole process involves the color model conversion (from RGB to HSV, RGB to grayscale), image smoothing (bilateral filtering), thresholding (OTSU adaptive threshold), image enhancement (morphological operation), contour findings, edge detection (Canny edge) and segmentation measurement. Through a combination of those methods in each step, we finally manage to extract the board from the background, detect all the transmission lines and measure their size. The size is measured in pixels rather than the actual length.
author2 Tan Eng Leong
author_facet Tan Eng Leong
Zheng, Yu
format Thesis-Master by Coursework
author Zheng, Yu
author_sort Zheng, Yu
title Image processing for transmission line extraction and detection
title_short Image processing for transmission line extraction and detection
title_full Image processing for transmission line extraction and detection
title_fullStr Image processing for transmission line extraction and detection
title_full_unstemmed Image processing for transmission line extraction and detection
title_sort image processing for transmission line extraction and detection
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/161262
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