There are a number of studies that deal with detection of road network from image Remote Sensing data. However, little work has been done on algorithms for horizontal road signs detection from Remote Sensing data. On the other hand there are many papers that deal with horizontal road signs detection in the field of Computer vision. Theoretical part of master thesis sumarizes the methods that are used to detect objects from both, Remote Sensing and Computer vision data. In the practical part an algorithm of automatic Zebra-crossing detection based on Aerial Images and vector road layer is designed. Zebra-crossings are detected using matching of image with set of predefined patterns. Obtained set of potential objects is then filtred using geometric and relational criteria. At the end of this thesis, the proposed algorithm is validated and the results are discussed with literature. Key words: Zebra-crossing, Horizontal road signs, Image matching, Aerial images
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:368074 |
| Date | January 2017 |
| Creators | Tomíček, Jiří |
| Contributors | Potůčková, Markéta, Fiala, Radek |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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