Multi-feature Method: An integrated content based image retrieval system
Inhaltsverzeichnis
Referenz
Chen Liu; Zhou Wei: Multi-feature Method: An integrated content based image retrieval system Intelligence Information Processing and Trusted Computing (IPTC), 2011 2nd International Symposium on , pp.43-46, 22-23 Oct. 2011
DOI
http://dx.doi.org/10.1109/IPTC.2011.18
Abstract
The process of retrieving desired or similar images from a large collection of images on the basis of features is referred as Content Based Image Retrieval (CBIR). In this paper, a integrated CBIR system is proposed using combined features and weighted similarity. The features include visual features of color, texture and shape and key text metadata. Some experimental simulations have been presented to show the accuracy and efficiency of the proposed retrieval method.
Extended Abstract
Bibtex
@INPROCEEDINGS{6103532,
author={C. Liu and Z. Wei},
booktitle={Intelligence Information Processing and Trusted Computing (IPTC), 2011 2nd International Symposium on},
title={Multi-feature Method: An Integrated Content Based Image Retrieval System},
year={2011},
pages={43-46},
keywords={content-based retrieval;feature extraction;image colour analysis;image retrieval;image texture;meta data;color visual features;combined features;integrated CBIR system;integrated content based image retrieval system;key text metadata;multifeature method;shape features;texture features;weighted similarity;Color;Histograms;Image color analysis;Image edge detection;Image retrieval;Shape;CBIR;QBIC;feature retrieval;multi-feature},
doi={10.1109/IPTC.2011.18},
url={http://dx.doi.org/10.1109/IPTC.2011.18 http://de.evo-art.org/index.php?title=Multi-feature_Method:_An_integrated_content_based_image_retrieval_system },
month={Oct},
}
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