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

Juan Gu; Jun Chen; Qiming Zhou

doi:10.1117/12.655211

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

Juan Gu^*, Jun Chen, Qiming Zhou

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

1 Citation (Scopus)

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.

Original language	English
Article number	60441B
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	6044
DOIs	https://doi.org/10.1117/12.655211
Publication status	Published - 2005
Event	MIPPR 2005: Image Analysis Techniques - Wuhan, China Duration: 31 Oct 2005 → 2 Nov 2005

User-Defined Keywords

FNEA
High resolution remotely sensed imagery
Image segmentation
Information extraction

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10.1117/12.655211

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title = "Image segmentation - Its application to information extraction for updating geo-spatial databases",

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.",

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AU - Chen, Jun

AU - Zhou, Qiming

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AB - 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.

KW - FNEA

KW - High resolution remotely sensed imagery

KW - Image segmentation

KW - Information extraction

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U2 - 10.1117/12.655211

DO - 10.1117/12.655211

M3 - Conference article

AN - SCOPUS:33644959702

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VL - 6044

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

M1 - 60441B

T2 - MIPPR 2005: Image Analysis Techniques

Y2 - 31 October 2005 through 2 November 2005

ER -

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

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