Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/68532
Title: Robust feature detection and tracking in thermal-infrared video
Authors: Vu Hoang Minh
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2016
Abstract: 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.
URI: http://hdl.handle.net/10356/68532
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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