Image detection program method C improvement

Method C is the new, fast but simple program which written by the project group in Rolls – Royce@NTU Corporate Lab. The method uses the knowledge of Discrete Fourier Transform (DFT), Gaussian filtering and selecting threshold value to detect the topographic and crystallographic defects. But it has s...

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Main Author: Zhang, Meixia
Other Authors: Chia Liang Tien
Format: Final Year Project
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/10356/70257
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-702572023-03-03T20:46:52Z Image detection program method C improvement Zhang, Meixia Chia Liang Tien School of Computer Science and Engineering Rolls-Royce@NTU Corporate Lab DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Method C is the new, fast but simple program which written by the project group in Rolls – Royce@NTU Corporate Lab. The method uses the knowledge of Discrete Fourier Transform (DFT), Gaussian filtering and selecting threshold value to detect the topographic and crystallographic defects. But it has some limitations to detect the crystallographic defects. This project is supported by the project group of Rolls – Royce@NTU Corporate Lab. The programming language used in this project is MatLab. The purpose of this project is to improve Method C to deal with crystallographic defects. The basic processes for the project are analyzing the image sets, learning Method C, selecting suitable parameters for Method C, and 3 experiments to select the input image for detection. Finally, the improved Method C can detect the crystallographic defects – HAB and Rx. For fu rther improvement, can classify the types of detected noised and remove them for increasing accuracy. Bachelor of Engineering (Computer Science) 2017-04-18T02:19:09Z 2017-04-18T02:19:09Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70257 en Nanyang Technological University 50 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Zhang, Meixia
Image detection program method C improvement
description Method C is the new, fast but simple program which written by the project group in Rolls – Royce@NTU Corporate Lab. The method uses the knowledge of Discrete Fourier Transform (DFT), Gaussian filtering and selecting threshold value to detect the topographic and crystallographic defects. But it has some limitations to detect the crystallographic defects. This project is supported by the project group of Rolls – Royce@NTU Corporate Lab. The programming language used in this project is MatLab. The purpose of this project is to improve Method C to deal with crystallographic defects. The basic processes for the project are analyzing the image sets, learning Method C, selecting suitable parameters for Method C, and 3 experiments to select the input image for detection. Finally, the improved Method C can detect the crystallographic defects – HAB and Rx. For fu rther improvement, can classify the types of detected noised and remove them for increasing accuracy.
author2 Chia Liang Tien
author_facet Chia Liang Tien
Zhang, Meixia
format Final Year Project
author Zhang, Meixia
author_sort Zhang, Meixia
title Image detection program method C improvement
title_short Image detection program method C improvement
title_full Image detection program method C improvement
title_fullStr Image detection program method C improvement
title_full_unstemmed Image detection program method C improvement
title_sort image detection program method c improvement
publishDate 2017
url http://hdl.handle.net/10356/70257
_version_ 1759856038436143104