碩士 / 國立臺灣科技大學 / 電機工程系 / 104 / Global Positioning System (GPS) technology is fairly universal, but the satellite signal sometimes is not reliable by interference from the tall buildings, and can not be used indoors. In this thesis, we propose to use the visual beacons to position, instead of using GPS. The proposed method can achieve a differential wheeled robot autonomous navigation.In this thesis, using Speeded Up Robust Features (SURF) to identify visual beacon.But in order to accelerate image processing and increase the recognition rate, need to do image preprocessing. Based on the characteristics of every visual beacon, define suitable image preprocessing.
In this thesis, the experiment is executed on our campus. According to the environmental characteristics of the campus, set out distinctive visual beacons. Advance to detect visual beacons' interest points and descriptors, and store to pad's memory to facilitate the subsequent alignment use. And save time to detect interest points and extract their descriptors repeatedly. It's impotant to select right region of interest (ROI) . First, in the area of visual beacon that may appear in the image, select a wide range of the region of interest. Second, if visual beacon has significant visual color characteristics, and then detect the color of a real region of interest. This not only speeds up the image processing speed and increases the recognition rate. Further, there are many trees on our campus and the trees are thick with leaves. There is a large number of interest points come from those leaves. Need to spend a lot of time to compute. However, these interest points are not fixed, and can not be used. Therefore, this paper through the color detection to remove pixles of the leaves. Not only saves a lot of time in operation to detect interest points and extract descriptors, but also to enhance the recognition rate.
| Identifer | oai:union.ndltd.org:TW/104NTUS5442185 |
| Date | January 2016 |
| Creators | Shu-Fen Liu, 劉淑芬 |
| Contributors | Chung-Hsien Kuo, 郭重顯 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 76 |
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