NDLI: Statistical framework for content-based medical image retrieval based on wavelet orthogonal polynomial model with multiresolution structure

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Statistical framework for content-based medical image retrieval based on wavelet orthogonal polynomial model with multiresolution structure

Content Provider	Springer Nature Link
Author	Seetharaman, K. Kamarasan, M.
Copyright Year	2013
Abstract	This paper proposes wavelet based orthogonal polynomial coefficients model for content based image retrieval (CBIR). The coefficients are categorized into low-frequency and high-frequency based on a criteria. The criteria is adaptively determined and fixed according to the nature and structure of the image, because the wavelet based orthogonal polynomial model spatially localizes the frequency information. Wavelet packet and Daubechies-4 transforms are jointly used to construct both approximation (low-frequency) and detailed (high-frequency) multiresolution image subbands. Color feature are extracted from low-frequency subband based on color autocorrelogram, whereas texture features are extracted from high-frequency subband based on co-occurrence matrix. Based on these features, the feature vector is formed. The proposed CBIR method reduces the feature variation when different modalities of images are combined. The proposed system assessed two medical image databases and one general image database with Minkowski-form distance method. The experimental results show that the proposed method achieves comparable retrieval performance with medical dataset; moreover, it is very fast with low computational load. Further, the obtained results were compared with other recently developed methods such as highly adaptive wavelet method, Wavelet optimization method and effective CBIR techniques. The proposed method yields better results compared to that of existing methods.
Starting Page	53
Ending Page	66
Page Count	14
File Format	PDF
ISSN	21926611
Journal	International Journal of Multimedia Information Retrieval
Volume Number	3
Issue Number	1
e-ISSN	2192662X
Language	English
Publisher	Springer London
Publisher Date	2013-11-02
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Wavelet transform Information Storage and Retrieval Data Mining and Knowledge Discovery Autocorrelogram Multimedia Information Systems GLCM Orthogonal polynomial Multiresolution CBIR Wavelet packet Image Processing and Computer Vision Computer Science Information Systems Applications (incl. Internet)
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences Information Systems Media Technology

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