Content based image retrieval using color, texture and shape features
Inhaltsverzeichnis
Referenz
Hiremath, P.S.; Pujari, J.: Content based image retrieval using color, texture and shape features. Advanced Computing and Communications, 2007. ADCOM 2007. International Conference on , pp.780-784, 18-21 Dec. 2007.
DOI
http://dx.doi.org/10.1109/ADCOM.2007.21
Abstract
Color, texture and shape information have been the primitive image descriptors in content based image retrieval systems. This paper presents a novel framework for combining all the three i.e. color, texture and shape information, and achieve higher retrieval efficiency. The image is partitioned into non- overlapping tiles of equal size. The color moments and moments on Gabor filter responses of these tiles serve as local descriptors of color and texture respectively. This local information is captured for two resolutions and two grid layouts that provide different details of the same image. An integrated matching scheme, based on most similar highest priority (MSHP) principle and the adjacency matrix of a bipartite graph formed using the tiles of query and target image, is provided for matching the images. Shape information is captured in terms of edge images computed using gradient vector flow fields. Invariant moments are then used to record the shape features. The combination of the color, texture and shape features provide a robust feature set for image retrieval. The experimental results demonstrate the efficacy of the method.
Extended Abstract
Bibtex
@INPROCEEDINGS{4426062,
author={P. S. Hiremath and J. Pujari},
booktitle={Advanced Computing and Communications, 2007. ADCOM 2007. International Conference on},
title={Content Based Image Retrieval Using Color, Texture and Shape Features},
year={2007},
pages={780-784},
keywords={Gabor filters;content-based retrieval;gradient methods;graph theory;image colour analysis;image matching;image retrieval;image texture;Gabor filter response;bipartite graph;color information;content based image retrieval;gradient vector flow field;integrated matching scheme;invariant moments;most similar highest priority principle;shape information;texture information;Computer science;Content based retrieval;Horses;Humans;Image retrieval;Image segmentation;Information retrieval;Robustness;Shape;Tiles},
doi={10.1109/ADCOM.2007.21},
url={http://dx.doi.org/10.1109/ADCOM.2007.21 http://de.evo-art.org/index.php?title=Content_based_image_retrieval_using_color,_texture_and_shape_features },
month={Dec},
}
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