Height estimation for buildings in monocular satellite/airborne images based on fuzzy reasoning and genetic algorithm

Author

Izadi, Mohammad ; Saeedi, Parvaneh

Author_Institution

Sch. of Eng. Sci., Simon Fraser Univ., Burnaby, BC

fYear

2009

fDate

6-8 May 2009

Firstpage

125

Lastpage

128

Abstract

This paper presents a height estimation method for buildings with polygonal footprints in monocular satellite/airborne images by combining fuzzy reasoning and genetic algorithm. A fitness function is employed using a set of fuzzy rules that assess various height hypothesis candidates for each building. A genetic algorithm is utilized that optimizes the fitness function to recover the most accurate height quickly with an accuracy that is independent of the acquisition method. Experimental results verify the effectiveness of the proposed method, with an overall mean height error of 35 cm.

Keywords

fuzzy set theory; genetic algorithms; image reconstruction; inference mechanisms; fitness function; fuzzy reasoning; genetic algorithm; height estimation method; monocular satellite/airborne images; polygonal footprints; Buildings; Fuzzy reasoning; Genetic algorithms; Genetic engineering; Geometry; Image reconstruction; Image segmentation; Satellites; Shape; Sun;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Analysis for Multimedia Interactive Services, 2009. WIAMIS '09. 10th Workshop on

Conference_Location

London

Print_ISBN

978-1-4244-3609-5

Electronic_ISBN

978-1-4244-3610-1

Type

conf

DOI

10.1109/WIAMIS.2009.5031448

Filename

5031448