A genetic algorithm-based satellite image retrieval model

被引：0

作者：

Huang, Yo-Ping ^{[1
]}

Chang, Tsun-Wei ^{[1
]}

Liu, Dankai ^{[1
]}

机构：

[1] Tatung Univ, Dept Comp Sci & Engn, Taipei 10451, Taiwan

来源：

EISTA '06: 4TH INT CONF ON EDUCATION AND INFORMATION SYSTEMS: TECHNOLOGIES AND APPLICAT/SOIC'06: 2ND INT CONF ON SOCIAL AND ORGANIZATIONAL INFORMATICS AND CYBERNETICS, VOL II | 2006年

关键词：

satellite image; early-warning system; genetic algorithm; image retrieval; relevance feedback;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Using remote sensing data to construct an early-warning mechanism deserves an ever-lasting investigation. An early-warning system can protect the human life and reduce the property damage. The main goal of this paper is to build a disaster early-warning system based on the information extracted from satellite image data. A genetic algorithm-based image retrieval model is proposed to search for specific events in the satellite images. The accessibility of satellite images is achieved through the genetic operations. The retrieval accuracy can be further improved by the proposed relevance feedback. Detailed methodology is described in this paper. The experimental results demonstrate a satisfactory retrieval efficiency from the proposed model.

引用

页码：123 / +

页数：3

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