Statistical Shape Features in Content-Based Image Retrieval
Inhaltsverzeichnis
Referenz
Jorma Laaksonen, Erkki Oja and Sami Brandt: Statistical Shape Features in Content-Based Image Retrieval. In Proceedings of the 15th International Conference on Pattern Recognition, Vol.2, pp. 1062 - 1065, Sep 2000
DOI
http://dx.doi.org/10.1109/ICPR.2000.906258
Abstract
In this article the use of shape features in content-based image retrieval is studied. The emphasis is on techniques which do not demand object segmentation. PicSOM, the image retrieval system used in the experiments, requires that features are represented by constant-sized feature vectors for which the Euclidean distance can be used as a similarity measure. The shape features suggested here are edge histograms and Fourier transform based features computed for an edge image in Cartesian and polar coordinate planes. The results show that both local and global shape features are important clues of shapes in an image
Extended Abstract
Bibtex
@INPROCEEDINGS{906258,
author={S. Brandt and J. Laaksonen and E. Oja},
booktitle={Pattern Recognition, 2000. Proceedings. 15th International Conference on},
title={Statistical shape features in content-based image retrieval},
year={2000},
volume={2},
pages={1062-1065 vol.2},
keywords={Fourier transforms;edge detection;feature extraction;image retrieval;search engines;statistical analysis;visual databases;Euclidean distance;Fourier transform;PicSOM;content-based image retrieval;edge detection;edge histograms;feature vectors;image database;search engine;statistical shape features;Content based retrieval;Feature extraction;Histograms;Image databases;Image retrieval;Image segmentation;Laboratories;Search engines;Shape;Spatial databases},
doi={10.1109/ICPR.2000.906258},
url={http://dx.doi.org/10.1109/ICPR.2000.906258 http://de.evo-art.org/index.php?title=Statistical_Shape_Features_in_Content-Based_Image_Retrieval },
ISSN={1051-4651},
month={},
}
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