Skip navigation
Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/5728
Title: Local extrema co-occurrence pattern for color and texture image retrieval
Authors: Verma M.
Raman, Balasubramanian
Murala S.
Published in: Neurocomputing
Abstract: A real world problem of image retrieval and searching is considered in this paper. In modern generation, managing images from a large storage medium is not a straightforward job. Many researchers have worked on texture features, and produced diverse feature descriptors based on uniform, rotation invariant, edges and directional properties. However, most of them convert the relationship of the center pixel and the boundary pixel into a local pattern, and use histogram to represent the local pattern as a feature vector. In this work, we propose a new image retrieval technique; local extrema co-occurrence patterns (LECoP) using the HSV color space. HSV color space is used in this method to utilize the color, intensity and brightness of images. Local extrema patterns are applied to define the local information of image, and gray level co-occurrence matrix is used to obtain the co-occurrence of LEP map pixels. The local extrema co-occurrence pattern extracts the local directional information from local extrema pattern, and convert it into a well-mannered feature vector with use of gray level co-occurrence matrix. The presented method is tested on five standard databases called Corel, MIT VisTex and STex, in which Corel database includes Corel-1k, Corer-5k and Corel-10k databases. Also, this algorithm is compared with previous proposed methods, and results in terms of precision and recall are shown in this work. © 2015 Elsevier B.V.
Citation: Neurocomputing (2015), 165(): 255-269
URI: https://doi.org/10.1016/j.neucom.2015.03.015
http://repository.iitr.ac.in/handle/123456789/5728
Issue Date: 2015
Publisher: Elsevier
Keywords: Corel database
Gray level co-occurrence matrix
Local extrema co-occurrence pattern
Local extrema patterns
MIT VisTex database
STex database
ISSN: 9252312
Author Scopus IDs: 56405124100
23135470700
26639647100
Author Affiliations: Verma, M., Department of Mathematics, Indian Institute of Technology Roorkee, Uttarakhand, India
Raman, B., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Uttarakhand, India
Murala, S., Department of Electrical Engineering, Indian Institute of Technology Ropar, Rupnagar, Punjab, India
Funding Details: This work was supported by the Ministry of Human Resource and Development (MHRD) Grant, India under Grant MHRD-02-23-200-304 . Authors would like to thank the associate editor and anonymous reviewers for thoughtful comments and valuable suggestions to improve the quality, which have been incorporated in this paper. Manisha Verma was born in India in 1989. She received the B.Sc. degree from Maharani?s College, Rajasthan University, Jaipur, India in 2009, the M.Sc. degree in Industrial Mathematics and Informatics from the Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, India in 2012. Currently, she is pursuing her Ph.D. in the Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, India. Her major area of interests are content based image retrieval, face and palmprint recognition, and object tracking. Balasubramanian Raman is an associate professor in the Department of Computer Science and Engineering at Indian Institute of Technology Roorkee from 2013. He has obtained M.Sc. degree in Mathematics from Madras Christian College, University of Madras in 1996 and Ph.D. from Indian Institute of Technology Madras in 2001. He was a post-doctoral fellow at the University of Missouri Columbia, USA in 2001–2002 and a post-doctoral associate at Rutgers, the State University of New Jersey, USA in 2002–2003. He joined Department of Mathematics at Indian Institute of Technology Roorkee as a lecturer in 2004 and became an assistant professor in 2006 and an associate professor in 2012. He was a visiting professor and a member of Computer Vision and Sensing Systems Laboratory in the Department of Electrical and Computer Engineering at University of Windsor, Canada during May–August 2009. His area of research includes vision geometry, digital watermarking using mathematical transformations, image fusion, biometrics and secure image transmission over wireless channel, content based image retrieval and hyperspectral imaging. Subrahmanyam Murala was born in India in 1985. He received the B.E. degree in Electrical and Electronics Engineering from Andhra University, Andhra Pradesh, India in 2007. Afterwards, he received his M.Tech. and Ph.D. degrees from the Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, India in 2009 and 2012 respectively. He was a post-doctoral researcher in the Department of Electrical and Computer Engineering at University of Windsor, Windsor, ON, Canada from July 01, 2012 to June 30, 2014. Currently, he is working as an assistant professor in the Department of Electrical Engineering, IIT Ropar, Rupnagar, Punjab, India. His major fields of interests are content based image retrieval, medical imaging and object tracking.
Corresponding Author: Verma, M.; Department of Mathematics, Indian Institute of Technology RoorkeeIndia
Appears in Collections:Journal Publications [CS]

Files in This Item:
There are no files associated with this item.
Show full item record


Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.