NDLI: Effective content-based image retrieval: Combination of quantized histogram texture features in the DCT domain

Content Provider	IEEE Xplore Digital Library
Author	Fazal-e-Malik Baharudin, B.
Copyright Year	2012
Description	Author affiliation: Department of Computer and Information Sciences, Universiti Teknologi PETRONAS, Malaysia (Fazal-e-Malik; Baharudin, B.)
Abstract	Effective Content-Based Image Retrieval (CBIR) is based on efficient low level features extraction for indexing and on effective query image matching with indexed images for retrieval of similar images. Feature extraction in compressed domain is an attractive area because at present almost all the images are represented in the compressed form using the DCT (Discrete Cosine Transformation) blocks transformation. Some critical information is removed in compression and only perceptual information is left which has significant attraction for information retrieval in the compressed domain. In this paper the statistical texture features are extracted from the quantized histograms in the DCT domain using only the DC and first three AC coefficients of the DCT blocks of image having more significant information. We study the effect of combination of texture features in effective image retrieval. We perform experimental comparison of combination of various statistical texture features to get the optimum combination of features for the effective image retrieval in terms of precision. Experiments on the Corel database using the proposed approach, give results which show that the combination of various features of quantized histograms give good performance in retrieval as compared to use single or less number of texture features combination.
Starting Page	425
Ending Page	430
File Size	2085774
Page Count	6
File Format	PDF
ISBN	9781467319379
e-ISBN	9781467319386
DOI	10.1109/ICCISci.2012.6297283
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-12
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Histograms Content-based image retrieval (CBIR) Statistical texture features DCT Quantized histogram Feature extraction Entropy Block transformation Standards
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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