A Universal Model for Content- Based Image Retrieval
Inhaltsverzeichnis
Referenz
S. Nandagopalan, Dr. B. S. Adiga, and N. Deepak: A Universal Model for Content- Based Image Retrieval. WASET, Vol.46, No.112, pp.644-647, 2008
DOI
Abstract
In this paper a novel approach for generalized image retrieval based on semantic contents is presented. A combination of three feature extraction methods namely color, texture, and edge histogram descriptor. There is a provision to add new features in future for better retrieval efficiency. Any combination of these methods, which is more appropriate for the application, can be used for retrieval. This is provided through User Interface (UI) in the form of relevance feedback. The image properties analyzed in this work are by using computer vision and image processing algorithms. For color the histogram of images are computed, for texture cooccurrence matrix based entropy, energy, etc, are calculated and for edge density it is Edge Histogram Descriptor (EHD) that is found. For retrieval of images, a novel idea is developed based on greedy strategy to reduce the computational complexity. The entire system was developed using AForge.Imaging (an open source product), MATLAB .NET Builder, C#, and Oracle 10g. The system was tested with Coral Image database containing 1000 natural images and achieved better results.
Extended Abstract
Bibtex
@article{
author = {S. Nandagopalan, Dr. B. S. Adiga, and N. Deepak},
title = {A Universal Model for Content- Based Image Retrieval},
journal = {WASET, World Academy of Science, Engineering and Technology International Journal of Computer, Electrical, Automation, Control and Information Engineering},
volume = {46},
number = {112},
pages = {644-647},
year = {2008},
doi={},
url={http://waset.org/publications/9436/a-universal-model-for-content-based-image-retrieval http://de.evo-art.org/index.php?title=A_Universal_Model_for_Content-_Based_Image_Retrieval},
}
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Links
Full Text
http://waset.org/publications/9436/a-universal-model-for-content-based-image-retrieval
