CMRT09

Stilla, Uwe

Bibliographic data

Monograph

Persistent identifier:: 856955019

Author:: Stilla, Uwe

Title:: CMRT09

Sub title:: object extraction for 3D city models, road databases, and traffic monitoring ; concepts, algorithms and evaluation ; Paris, France, September 3 - 4, 2009 ; [joint conference of ISPRS working groups III/4 and III/5]

Scope:: X, 234 Seiten

Year of publication:: 2009

Place of publication:: Lemmer

Publisher of the original:: GITC

Identifier (digital):: 856955019

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: COMPARISON OF METHODS FOR AUTOMATED BUILDING EXTRACTION FROM HIGH RESOLUTION IMAGE DATA G. Vozikis

Document type:: Monograph

Structure type:: Chapter

in: Stilla U, Rottensteiner F, Paparoditis N (Eds) CMRT09. IAPRS, Vol. XXXVIII, Part 3/W4 — Paris, France, 3-4 September, 2009 COMPARISON OF METHODS FOR AUTOMATED BUILDING EXTRACTION FROM HIGH RESOLUTION IMAGE DATA G. Vozikis GEOMET Ltd., Faneromenis 4, 15561 Holargos-Athens, GREECE george.vozikis@geomet.gr KEY WORDS: Photogrammetry, Building , Detection , Transformation, Model, Pattern ABSTRACT: This paper discusses a comparison analysis of different methods for automated building extraction from aerial and spacebome imagery. Particularly approaches employing the Hough Transformation, Pattern Recognition Procedures and Texture Analysis are examined. Throughout this investigation advantages and disadvantages of the mentioned methods are examined, in order to see which procedures are suitable for extracting the geometric building properties, and thus to automatically create a DCM (Digital City Model). The examined data sets consist of panchromatic imagery coming from both very high resolution satellites, as well as line scanning aerial sensors. A quantitative and qualitative assessment will help to evaluate the previously mentioned procedures. 1. INTRODUCTION Automated building extraction from high resolution image data (either airborne or spacebome) is becoming more and more mature. Everyday new techniques are investigated and the results are getting more and more reliable, while the degree of automation increases. Each building extraction method is of course coupled to certain pros and cons. The use of the Hough Transformation has proven to be a very promising tool in the frame of the automated creation of Digital City Models (DCMs), by extracting building properties from optical data. But also approaches based on Image Matching or Texture Analysis seem to provide usable results. A DCM is described through the outlines of buildings outlines of an urban area. Vertical walls are assumed, and the elevation information of these buildings can be taken from a DSM (Digital Surface Model). The creation of the DSM and the assignement of the elevation value is not discussed in this paper, thus when mentioning DCMs we actually mean the Model that holds the 2D outline-information of a building. The goal of this paper is to conclude for which kind of data sets and accuracy pretensions a certain approach is recommendable. Moreover, the reachable degree of automation is also examined, in order to see how reliable results are that were produced without human interaction. Table 1 : Examined data sets. Sensor Location GSD (m) Extents (km) ADS40 Valladolid, Spain 0.25 1 x 1 HRSC-AX Bern, Switzerland ca. 0.3 0.2 x 0.3 Quickbird Denver, USA 0.6 16.9 x 16.5 IKONOS Athens, Greece 1 9.7 x 12.3 Orb view 3 Orange, USA 1 0.6 x 0.7 Altogether, five different datasets, coming from airborne and spacebome sensors, were examined. These datasets depict urban regions with varying building sizes, patterns and densities. It should be mentioned here that only subsets have been used for the investigations. 2. DESCRIPTION OF WORKFLOWS 2.1 Hough Transformation The proposed workflow for automated building extraction from image data by employing the Hough Transformation has been thoroughly described in Vozikis (2004). Figure 1 shows the major steps of the process. Figure 1: Proposed workflow for automated building extraction from image data All steps in this workflow are highly automated and human interaction is reduced to a minimum. In the following the 4 major steps are briefly described.

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