Image segmentation: its application to information extraction for updating geo-spatial databases

Juan Gu; Jun Chen; Qiming Zhou

doi:10.1117/12.655211

3 November 2005 Image segmentation: its application to information extraction for updating geo-spatial databases

Juan Gu, Jun Chen, Qiming Zhou

Proceedings Volume 6044, MIPPR 2005: Image Analysis Techniques; 60441B (2005) https://doi.org/10.1117/12.655211
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China

Abstract

The unsatisfactory result of traditional pixel-based classification methods in classifying high resolution remotely sensed imagery may be improved by employing image segmentation. Based on a brief review of image segmentation, this paper introduces an image segmentation method--FNEA--which is used in eCognition, the first commercial object-oriented image processing software in the world, for automatic object extraction from high-resolution satellite images and automatic updating of GIS databases. From the point of information extraction, the author analyzes the advantages and disadvantages of the algorithm by using several examples and put forward possible improvements.

Citation Download Citation

Juan Gu, Jun Chen, and Qiming Zhou "Image segmentation: its application to information extraction for updating geo-spatial databases", Proc. SPIE 6044, MIPPR 2005: Image Analysis Techniques, 60441B (3 November 2005); https://doi.org/10.1117/12.655211

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