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Road Detection By Mean Shift Segmentation And Structural Analysis

Road extraction from satellite or aerial images is a popular issue in remote sensing. Extracted road maps or networks can be used in various applications. Normally, maps for roads are available in geographic information systems (GIS), however these informations are not being produced automatically. Generally they are formed with the aid of human. Road extraction algorithms are trying to detect the roads from satellite or aerial images with the minimum in-teraction of human. Aim of this thesis is to analyze a previously defined algorithm about road extraction and to present alternatives and possible improvements to this algorithm. The base-line algorithm and proposed alternative algorithm and steps are based on mean-shift segmen-tation procedure. Proposed alternative methods are generally based on structural features of the image. Firstly, fundamental definitions of applied algorithms and methods are explained, mathematical definitions and visual examples are given for better understanding. Then, the chosen baseline algorithm and its alternatives are explained in detail. After the presentation of alternative methods, experimental results and inferences which are obtained during the implementation and analysis of mentioned algorithms and methods are presented.

Identiferoai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12614443/index.pdf
Date01 June 2012
CreatorsDursun, Mustafa
ContributorsHalici, Ugur Prof. Dr.
PublisherMETU
Source SetsMiddle East Technical Univ.
LanguageEnglish
Detected LanguageEnglish
TypeM.S. Thesis
Formattext/pdf
RightsTo liberate the content for public access

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