Automatic extraction of building statistics from digital orthophotos

被引:29
作者
Stassopoulou, A [1 ]
Caelli, T
Ramirez, R
机构
[1] Ohio State Univ, Ctr Mapping, Columbus, OH 43212 USA
[2] Intercoll, CY-1700 Nicosia, Cyprus
[3] Univ Alberta, Dept Psychol, Computat Percept & Act Lab, Edmonton, AB, Canada
基金
美国国家航空航天局;
关键词
D O I
10.1080/136588100750022796
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 [计算机科学与技术];
摘要
In this paper we discuss uses of image segmentation, feature extraction and Bayesian networks for identifying buildings in digital orthophotos and the utilisation of the results for the automated computation of building statistics. Our work differs from previous attempts in a number of ways. Firstly, image segmentation is accomplished using an adaptive multi-scale method which brings together region and edge information to segment the image into regions. Secondly, automated building feature extraction (e.g. corners) is optimised to fit with expert human annotation performance. The third aspect of this work is the exploration of Bayesian networks as a method for fusing available information (ranging from corner information to solar angles as indicators of shadow location) to classify segmented regions as corresponding to buildings or not. Such processes then permit the automatic compilation of building statistics.
引用
收藏
页码:795 / 814
页数:20
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