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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/7416
Title: HOG feature and vocabulary tree for content-based image retrieval
Authors: Agarwal M.
Maheshwari R.P.
Published in: International Journal of Signal and Imaging Systems Engineering
Abstract: Histogram of Oriented Gradients (HOG) feature descriptor is very effective to represent objects and is widely used in human and face detection. In this paper, HOG feature descriptor is applied for Content-based Image Retrieval (CBIR). For handling similarity measurement of large amount of database, vocabulary tree is used. Experimental results illustrate the comparative analysis of retrieval system based on HOG feature descriptor and Gabor transform feature descriptor. It is verified that HOG-based retrieval system improves Average Precision (AP) and Average Recall (AR) (56.75% and 38.45%, respectively) from Gabor-transform-based retrieval system (41.20% and 25.41%, respectively). All the experiments are performed on Corel 1000 natural image database. Copyright © 2010 Inderscience Enterprises Ltd.
Citation: International Journal of Signal and Imaging Systems Engineering (2010), 3(4): 246-254
URI: https://doi.org/10.1504/IJSISE.2010.038020
http://repository.iitr.ac.in/handle/123456789/7416
Issue Date: 2010
Publisher: Inderscience Publishers
Keywords: CBIR
Content-based image retrieval
Gabor transform
Histogram of oriented gradient
HOG
Vocabulary tree
ISSN: 17480698
Author Scopus IDs: 36766911200
8941720600
Author Affiliations: Agarwal, M., Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee 247 667, Uttarakhand, India
Maheshwari, R.P., Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee 247 667, Uttarakhand, India
Corresponding Author: Agarwal, M.; Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee 247 667, Uttarakhand, India; email: meghagarwal29@gmail.com
Appears in Collections:Journal Publications [EE]

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