Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

Bibliographic data

Monograph

Persistent identifier:: 84098880X

Author:: Schreiber, Guido

Title:: Malerische Perspektive

Sub title:: mit einem Anhange über den Gebrauch geometrischer Grundrisse

Scope:: XVI, 248 Seiten

Year of publication:: 1854

Place of publication:: Karlsruhe

Identifier (digital):: 84098880X

Illustration:: Illustrationen, Diagramme

Signature of the source:: DG 5909

Language:: German

Publisher of the original:: Herder

Usage licence:: Public Domain Mark 1.0

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2015

Document type:: Monograph

Collection:: Mathematics

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Title:: Konstruktiver Theil.

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: Allgemeine Sätze.

Document type:: Monograph

Structure type:: Chapter

International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 7-4-3 W6, Valladolid, Spain, 3-4 June, 1999 * yft & 4. i "A\ Æ*l c. Patches from SPOT using REGSEG d. Patches from SPOT using OPTISEG Figure 6. Segmentation algorithm applied to SAR and SPOT. a. Patches from SAR using MUM b. Patches from SAR using RWSEG 4. POLYGON MATCHING The polygon matching method used in PAIRS and ARCHANGEL are based on the work of Abbasi-Dezfouli and Freeman (1994) and developed by Dowman et al. (1996). We describe here a new method which has similarities with these earlier methods. The method is summarised in Figure 7. In previous work (Dowman et al. 1996, Dowman, 1998) chain coding has been used. This technique is not used here, as studies showed that it did not add to the success of results achieved from the techniques in Figure 7. The use of a cost function for image matching was described by both Morgado and Dowman (1997) and Abbasi-Dezfouli and Freeman (1994). However, both of these authors found that there are some problems associated with its implementation. A general point was that on its own it will not differentiate all the good matches from the bad ones. This is because incorrect matches sometimes give a low value for the cost function, and correct matches sometimes give high values. Therefore, more information has to be used to improve the matching results, such as using a chain code method to describe the shapes of the patches, or using the relative geometry of the matched patches with respect to each other in order to highlight poor matches. Although it was shown that both of these methods worked in the examples cited by the authors, they would not necessarily work here. The use of the chain code method was ruled out above. The problem with using the relative geometry of matched patches is that there may not be enough good matches to ensure a reliable result could be determined, or too many bad but geometrically similar matches could easily lead to an incorrect result. Therefore, there is a question of robustness associated with these two methods of improving the match results.

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