Similarity Searching In Statistical Figures Based On Extracted Meta Data

Similarity searching is an excellent approach for getting information from subjective materials like images or videos. Some excellent works on special domains have done. We focus on statistical images. These kinds of images have some excellent features that can be clearly extractable and useable in...

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Bibliographic Details
Published inComputer Graphics, Imaging and Visualisation (CGIV 2007) pp. 329 - 334
Main Authors Hassan, M.M., Al Khatib, W.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2007
Subjects
Biomedical imaging
Computer science
Data mining
Feature extraction
Focusing
Histograms
Image analysis
Information extraction
Meta data
Petroleum
Prototypes
Shape
Similarity searching
Statistical images
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Summary:Similarity searching is an excellent approach for getting information from subjective materials like images or videos. Some excellent works on special domains have done. We focus on statistical images. These kinds of images have some excellent features that can be clearly extractable and useable in similarity searching. But there no significant work has been done in this area. So we have done some preliminary works in this domain. By some extensive analysis we classify images of this domain in some sub domains and also identified the nature of features those can be considered as silent. We develop a prototype based on this analysis where we store extracted features information of a statistical images as meta data. Then we devise some strategy to do similarity searching using standard query formulation.
ISBN:0769529283
9780769529288
DOI:10.1109/CGIV.2007.76