Robust feature detection and tracking in thermal-infrared video
In this thesis, popular techniques within the area of machine vision: noise reduction, feature detection, edge detection and feature tracking, have been studied. This project is concerned with the use of thermal-infrared cameras which are much less affected by changes in lighting, shadows and out-of...
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| Format: | Theses and Dissertations |
| Language: | English |
| Published: |
2016
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| Online Access: | http://hdl.handle.net/10356/68532 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | In this thesis, popular techniques within the area of machine vision: noise reduction, feature detection, edge detection and feature tracking, have been studied. This project is concerned with the use of thermal-infrared cameras which are much less affected by changes in lighting, shadows and out-of-view motion compared to visible cameras. The main research focus of this thesis is how to deal with the low signal-to-noise ratio of thermal-infrared video in developing a novel real-time methodology for robust feature detection and tracking. The thesis first reviews the background of thermal-infrared imagery. It then covers the necessity of a noise reduction filter in thermal-infrared video. Next, it presents a number of existing approaches in edge and feature detection followed by four proposed techniques. Finally, results reveal that the proposed techniques perform well in thermal-infrared video. |
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