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Reseach Article

An Efficient Image Retrieval Technique using Shape Context Feature

by Neha Bhuptani, Bijal Talati
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 98 - Number 1
Year of Publication: 2014
Authors: Neha Bhuptani, Bijal Talati
10.5120/17145-7163

Neha Bhuptani, Bijal Talati . An Efficient Image Retrieval Technique using Shape Context Feature. International Journal of Computer Applications. 98, 1 ( July 2014), 6-11. DOI=10.5120/17145-7163

@article{ 10.5120/17145-7163,
author = { Neha Bhuptani, Bijal Talati },
title = { An Efficient Image Retrieval Technique using Shape Context Feature },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 98 },
number = { 1 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 6-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume98/number1/17145-7163/ },
doi = { 10.5120/17145-7163 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:25:03.410277+05:30
%A Neha Bhuptani
%A Bijal Talati
%T An Efficient Image Retrieval Technique using Shape Context Feature
%J International Journal of Computer Applications
%@ 0975-8887
%V 98
%N 1
%P 6-11
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Increasing demands for image retrieval in field such as health informatics, biometrics, and crime prevention has forced developers to explore ways to manage and retrieve images more efficiently. An automated way to retrieve images based on the content or features of the images itself is provided by CBIR. Shape is one of key visual features used by human for distinguishing visual data along with other features of color and texture. Therefore, this work investigates one of the shape representation method shape context which helps in efficient CBIR. The main aim of this research is to look for and develop promising shape descriptor(s) which was found to be Shape Context for image retrieval and also to improve efficiency. The Shape context descriptor is contour based which focuses on irregular shapes. The time consuming step of shape context matching is reduced in this work up to approx. 48% on an average. The proposed work reduces the computational complexity maintaining its overall accuracy.

References
  1. Neha Bhuptani and Bjial Talati. Article: Variations in Shape Context Descriptor: A Survey. International Journal of Computer Applications 90(12):29-33, March 2014.
  2. Pooja, Chandan Singh. "An Effective Image Retrieval System using Region and Contour based Features. "
  3. Yang, Mingqiang, KidiyoKpalma, and Joseph Ronsin. "A survey of shape feature extraction techniques. " Pattern recognition (2008): 43-90.
  4. Zhang, Dengsheng, and Guojun Lu. "Review of shape representation and description techniques. " Pattern recognition 37, no. 1 (2004): 1-19.
  5. Belongie, Serge, Jitendra Malik, and Jan Puzicha. "Shape matching and object recognition using shape contexts. " Pattern Analysis and Machine Intelligence, IEEE Transactions on 24, no. 4 (2002): 509-522.
  6. Geevar, C. Zacharias, and P. Sojan Lal. "Combining Chain-Code and Fourier Descriptors for Fingerprint Matching. " Advances in Computing and Communications. Springer Berlin Heidelberg, 2011. 460-468.
  7. Schlosser S. , and Beichel, R. "Fast Shape Retrieval Based on Shape Contexts" In Image and Signal Processing and Analysis, 2009. ISPA 2009.
  8. Sarfraz, Muhammad, and A. Ridha. "Content-based image retrieval using multiple shape descriptors. " Computer Systems and Applications, 2007. AICCSA'07. IEEE/ACS International Conference on. IEEE, 2007.
  9. Lopez, Annet Deenu, Eldho S. Kollialil, and K. Gopika Gopan. "Adaptive Neuro-fuzzy Classifier for Weapon Detection in X-Ray Images of Luggage Using Zernike Moments and Shape Context Descriptor. " Advances in Computing and Communications (ICACC), 2013 Third International Conference on. IEEE, 2013.
  10. Wang, Zhiyong, et al. "Leaf Image Classification with Shape Context and SIFT Descriptors. " Digital Image Computing Techniques and Applications (DICTA), 2011 International Conference on. IEEE, 2011.
  11. Rusiñol, Marçal, and JosepLladós. "Efficient logo retrieval through hashing shape context descriptors. " In Proceedings of the 9th IAPR International Workshop on Document Analysis Systems, pp. 215-222. ACM, 2010.
  12. Image dataset of MPEG7 [Online] http://www. imageprocessinglace. com/root_files_V3/image_databases. htm
Index Terms

Computer Science
Information Sciences

Keywords

Shape Context Content based image retrieval Improved shape context Contour based methods Object recognition.