A comparative study of edge detection techniques for AI-based image recognition
Artificial Intelligence (AI) is currently the hottest technology in computer science. It is composed of different fields, such as machine learning, computer vision, etc. In general, a major goal of artificial intelligence research is to enable machines to perform complex tasks that normally require...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/141301 |
| _version_ | 1811691861246476288 |
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| author | Wang, Di |
| author2 | Meng-Hiot Lim |
| author_facet | Meng-Hiot Lim Wang, Di |
| author_sort | Wang, Di |
| collection | NTU |
| description | Artificial Intelligence (AI) is currently the hottest technology in computer science. It is composed of different fields, such as machine learning, computer vision, etc. In general, a major goal of artificial intelligence research is to enable machines to perform complex tasks that normally require human intelligence to complete. The development of these machines has benefited people's lives. One of the most important steps in the robot's execution of the task is target recognition. In this project, basic image recognition for target recognition is studied. This topic has studied image recognition through two aspects. The first aspect is edge extraction, and the second aspect is training neural networks for image recognition.
In this project, different edge detection technologies are studied. We use digital image processing methods to compare several edge detection technologies and observe the effects of different edge shapes, noise and other external factors on their detection results. Finally find the most suitable edge extraction technology for the subject.
At the same time, we used neural networks to identify the targets in the image and compared the impact of different sizes of training data on the testing results.
Key words: edge extraction, neural network, image recognition |
| first_indexed | 2024-10-01T06:26:37Z |
| format | Thesis-Master by Coursework |
| id | ntu-10356/141301 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:26:37Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1413012023-07-04T16:49:08Z A comparative study of edge detection techniques for AI-based image recognition Wang, Di Meng-Hiot Lim School of Electrical and Electronic Engineering EMHLIM@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Artificial Intelligence (AI) is currently the hottest technology in computer science. It is composed of different fields, such as machine learning, computer vision, etc. In general, a major goal of artificial intelligence research is to enable machines to perform complex tasks that normally require human intelligence to complete. The development of these machines has benefited people's lives. One of the most important steps in the robot's execution of the task is target recognition. In this project, basic image recognition for target recognition is studied. This topic has studied image recognition through two aspects. The first aspect is edge extraction, and the second aspect is training neural networks for image recognition. In this project, different edge detection technologies are studied. We use digital image processing methods to compare several edge detection technologies and observe the effects of different edge shapes, noise and other external factors on their detection results. Finally find the most suitable edge extraction technology for the subject. At the same time, we used neural networks to identify the targets in the image and compared the impact of different sizes of training data on the testing results. Key words: edge extraction, neural network, image recognition Master of Science (Computer Control and Automation) 2020-06-06T12:58:19Z 2020-06-06T12:58:19Z 2020 Thesis-Master by Coursework https://hdl.handle.net/10356/141301 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Wang, Di A comparative study of edge detection techniques for AI-based image recognition |
| title | A comparative study of edge detection techniques for AI-based image recognition |
| title_full | A comparative study of edge detection techniques for AI-based image recognition |
| title_fullStr | A comparative study of edge detection techniques for AI-based image recognition |
| title_full_unstemmed | A comparative study of edge detection techniques for AI-based image recognition |
| title_short | A comparative study of edge detection techniques for AI-based image recognition |
| title_sort | comparative study of edge detection techniques for ai based image recognition |
| topic | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence |
| url | https://hdl.handle.net/10356/141301 |
| work_keys_str_mv | AT wangdi acomparativestudyofedgedetectiontechniquesforaibasedimagerecognition AT wangdi comparativestudyofedgedetectiontechniquesforaibasedimagerecognition |