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

CMRT09: Object Extraction for 3D City Models, Road Databases and Traffic Monitoring - Concepts, Algorithms, and Evaluation the highest frequency of the signal.”). For our situation it means that sensor’s geometric resolution determines the object resolution, or in other words, the level of detail of the object. Table2: Quantitative results. scale A B B C C type urban low urban low urban low urban low urban sensors airborne airborne space bome space bome space bome method Seeding Seeding Seeding Matching Texture Analysis CFB 80.5% 90.2% 97% 88.3% 34.4% NFB 19.5% 9.8% 3% 11.7% 65.6% WFB 7.3% 4.8% 30.3% 1.7% 17.2% 3.2 Qualitative Assessment of Building Extraction The qualitative analysis is based on a comparison between the building outlines derived by using the proposed automated methodology, and manually mapped buildings (image restitution). The manual mapping is carried out by a professional operator who performs 2D (or 3D) digitization on the input data (oriented imagery or orthophotos). The residuals of each building comer from the manual mapping and the closest point of the automatically extracted shape are computed as a quality measure. The results are categorized in three groups depending on the method used for building extraction (Table 3). The RMS is given in pixels. Table3: Qualitative results. Hough Matching Texture Analysis RMS x 0.937 0.898 0.954 RMS y 0.914 0.958 0.996 total RMS 1.309 1.313 1.379 The number of examined objects is the same as in the quantitative analysis. Note that the figures in Table 3 are based on image residuals. They show the difference of the automatically derived comer points and the digitized ones in the image. As our data sets were acquired with vertical viewing angles these results can be also interpreted as planimetric object space residuals. But when dealing with images that were captured with oblique viewing angles, the buildings must be projected into object space in order to carry out a qualitative analysis in the reference system. 4. CONCLUSIONS The aim of this work was to propose a method for generating DCMs which makes use of images from spacebome or airborne line scanning devices, on orthophotos if available and on elevation models. Various image processing techniques, such as Hough transformation, adaptive region growing, image matching, texture analysis, were employed and investigated for deriving the strengths and weaknesses of each. A variety of data sets were tested, coming from both spacebome and airborne acquisition systems. Through the research based on adaptive region growing and on the iterative Hough transformation we can conclude that the method is very powerful, but has also some weaknesses. One is the high dependence on the radiometric quality of the input imagery. Furthermore, rather small buildings will not be treated correctly. Image matching proved to be a very effective, but very time consuming. The suggested strategy of texture analysis, although very efficient for pattern recognition over areas in small scale imagery, was not very successful for extracting individual buildings. Through this research partly very good results were obtained, but nevertheless further investigations are necessary for improving the quality of the results even more. Future work will be focused on: • Extraction of objects with holes (e.g. houses with inner courtyards), i.e. deriving the inner and outer boundary of buildings. • Research on constraint settings for aggregating neighbouring roof parts that belong to one building. • Introduction of multispectral information for making the algorithms more efficient, especially as far as seed point determination is concerned. • Extract edges on sub-pixel bases. • Integrate a hierarchical approach in order to decrease computation time. 5. REFERENCES Gong, P., Marceau, D.J. and Howarth, P.J., 1992. A Comparison of Spatial Feature Extraction Algorithms for Land- Use Classification with SPOT HRV Data. Remote Sensing of Environment, Vol. 40, pp. 137-151. Gonzalez, R.C., and Woods, R.E., 1992. Digital Image Processing. Reading, MA: Addison Wesley. Gonzalez, R.C. and Woods, R.E., 2002. Digital Image Processing, Second Edition. Patience Hall, New Jersey, 799 pages. Haralick, R.M., 1979. Statistical and Structural Approaches to Texture. Proceedings IEEE, Vol. 67, No.5, pp. 786-804. Kraus, K., 1996. Photogrammetrie, Band2, Verfeinerte Methoden und Anwendungen. Duemmler Verlag, Bonn, 488 pages. Scholten, F. and Gwinner, K., 2003. Band 12 "Publikationen der Deutschen Gesellschaft fur Photogrammetrie, Femerkundung und Geoinformation", Bochum, pp. 419-426. Vozikis, G., Jansa, J. and Fraser, C., 2003. Alternative Sensor Orientation Models for High-Resolution Satellite Imagery. Band 12 "Publikationen der Deutschen Gesellschaft fur Photogrammetrie, Femerkundung und Geoinformation", Bochum , pp. 179- 186. Vozikis, G., 2004: Automatic Generation and Updating of Digital City Models using High-Resolution Line-Scanning Systems. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 34, Part XXX. Vozikis, G. and Jansa, J., 2008. Advantages and Disadvantages of the Hough Transformation in the frame of Automated Building Extraction. International Society for Photogrammetry and Remote Sensing XXIst Congress, Beijing, China; 07-03- 2008 - 07-11-2008; in: "Proceedings", Vol. XXXVII. Part B3b (2008), ISSN: 1682-1750; 719 - 724. Zhang, Y. (2001): A Spectral and Spatial Information Integrated Approach for Tree Extraction from High-Resolution Digital Imagery. Digital Earth, Fredericton, Canada, 9 pages.

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