Title :
A system to detect houses and residential street networks in multispectral satellite images
Author :
Ünsalan, Cem ; Boyer, Kim L.
Author_Institution :
Dept. of Electr. & Electron. Eng., Yeditepe Univ., Turkey
Abstract :
Maps are vital tools for most government agencies and consumers. However, their manual generation and updating is tedious and time consuming. As a step toward automatic map generation, we introduce a novel system to detect houses and street networks in IKONOS multispectral images. Our system consists of four main blocks: multispectral analysis to detect cultural activity, segmentation of possible human activity regions, decomposition of segmented images, and graph theoretical algorithms to extract the street network and to detect houses over the decompositions. We tested our system on a large and diverse data set. Our results indicate the usefulness of our system in detecting houses and street networks, hence generating automated maps.
Keywords :
graph theory; image segmentation; object detection; spectral analysis; IKONOS multispectral images; automatic map generation; graph theoretical algorithms; house detection; image decomposition; image segmentation; multispectral analysis; multispectral satellite images; residential street network detection; Algorithm design and analysis; Cultural differences; Data mining; Government; Humans; Image analysis; Image segmentation; Multispectral imaging; Satellites; System testing;
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
Print_ISBN :
0-7695-2128-2
DOI :
10.1109/ICPR.2004.1334466