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Reseach Article

Semantic Indexing based Remote Sensing Image Retrieval: An Intelligent Decomposition Approach

by Kiran Ashok Bhandari, Manthalkar Ramchandra R
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 19
Year of Publication: 2013
Authors: Kiran Ashok Bhandari, Manthalkar Ramchandra R

Kiran Ashok Bhandari, Manthalkar Ramchandra R . Semantic Indexing based Remote Sensing Image Retrieval: An Intelligent Decomposition Approach. International Journal of Computer Applications. 74, 19 ( July 2013), 7-17. DOI=10.5120/13000-0004

@article{ 10.5120/13000-0004,
author = { Kiran Ashok Bhandari, Manthalkar Ramchandra R },
title = { Semantic Indexing based Remote Sensing Image Retrieval: An Intelligent Decomposition Approach },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 19 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 7-17 },
numpages = {9},
url = { },
doi = { 10.5120/13000-0004 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T21:42:42.462617+05:30
%A Kiran Ashok Bhandari
%A Manthalkar Ramchandra R
%T Semantic Indexing based Remote Sensing Image Retrieval: An Intelligent Decomposition Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 19
%P 7-17
%D 2013
%I Foundation of Computer Science (FCS), NY, USA

Without formulating physical contact with the object, Remote sensing is the achievement of information about an object or phenomenon. The contact of remote sensing (RS) images will turn into more complicated due to the vast data quantity, to defeat this challenges the users can admittance remote sensing images based on semantics. In the existing method, the Quin-tree is used for the decomposition of Content Based Image Retrieval in Remote Sensing, but it has poor retrieval accuracy. So the intelligent decomposition phase is used in our proposed method, which decomposes the image based on the spatial-spectral heterogeneity. The proposed method will perform visual feature, object semantic, spatial relationship semantic, scene semantic based retrievals to ensure fine retrieval schema, which will obtained by applying mapping and the SS modelling in the decomposed remote sensing image. The human intervention will be introduced in the system to ensure the high retrieval accuracy. The implementation result shows the effectiveness of proposed technique, in segmenting the text lines from the input document. The performance of the proposed method is evaluated by comparing the result of proposed method with the conventional SBRSIR technique. The comparison result shows that our proposed method more accurately retrieves the images based on the VF, OS and SS than the conventional SBRSIR technique.

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Index Terms

Computer Science
Information Sciences


CBIR Remote sensing (RS) images Visual Features (VF) Object Semantics Watershed Segmentation SVM Attribute Relational Graph (ARG) Spatial-spectral Heterogeneity Scene Matching model