An Approach for Similarity Matching and Comparison in Content Based Image Retrieval System

Authors

  • Numa Bajaj Department of Computer Science and Engineering, CGC College of Engineering, Mohali, India
  • Jagbir Singh Gill Department of Computer Science and Engineering, CGC College of Engineering, Mohali, India
  • Rakesh Kumar Department of Computer Science and Engineering, Sachdeva Engineering College, Mohali, India

DOI:

https://doi.org/10.37591/joipprp.v2i3.492

Keywords:

CBIR, HSV, recall, precision, database

Abstract

Today, in the age of images and digitization relevant retrieval is quite a topic of research. With every new day thousands of pictures are getting added into the database making it a high dimensional data set. Therefore, from a high dimensional dataset to get a set of relevant images is quite a cumbersome task. In this paper, experiment has been performed on the trademark images. Trademark is a very important asset for any organization and increasing trademark images have developed a quick need to organize these images. This paper includes the implementation of HSV model for fast retrieval which use color and texture so as to extract feature vector. Experiment takes query image and retrieve twelve most relevant images to the user. Further for performance evaluation parameter used is Precision and Recall.

Cite this Article
Numa Bajaj, Jagbir Singh Gill, Rakesh Kumar. An Approach for Similarity Matching and Comparison in Content Based Image Retrieval System. Journal of Image Processing & Pattern Recognition Progress. 2015; 2(3): 57–63p.

Author Biographies

  • Numa Bajaj, Department of Computer Science and Engineering, CGC College of Engineering, Mohali, India
    M.Tech Student, Computer Science Department
  • Jagbir Singh Gill, Department of Computer Science and Engineering, CGC College of Engineering, Mohali, India
    Assistant Professor, Computer Science Department
  • Rakesh Kumar, Department of Computer Science and Engineering, Sachdeva Engineering College, Mohali, India
    Dean and Associate Professor, Computer Science Department

References

Huang J, Kumar SR, Mitra M et al. Spatial color indexing and applications. International Journal of Computer Vision. 1999; 35(3): 245–268p.

Hiremath PS, Pujari J. Content based image retrieval using color, texture and shape features. In Advanced Computing and Communications ADCOM 2007. 2007; 780–784p.

Song YJ, Park WB, Kim DW et al. Content-based image retrieval using new color histogram. In Intelligent Signal Processing and Communication Systems ISPACS. 2004; 609–611p.

Murala S, Gonde AB, Maheshwari RP. Color and texture features for image indexing and retrieval. In Advance Computing Conference. 2009; 1411–1416p.

Kekre HB, Sonawane K. Comparative study of color histogram based bins approach in RGB, XYZ, Kekre's LXY and L′ X′ Y′ color spaces. In Circuits, Systems, Communication and Information Technology Applications (CSCITA). 2014; 364–369p.

Ketenci S, Gencturk B. Performance analysis in common color spaces of 2D gaussian color model for skin segmentation. In EUROCON. 2013; 1653–1657p.

Manjunath BS, Ohm JR, Vasudevan VV et al. Color and texture descriptors. Circuits and Systems for Video Technology, IEEE Transactions. 2001; 11(6): 703–715p.

Zhao Q, Yang J, Yang J et al. Stone images retrieval based on color histogram. In Image Analysis and Signal Processing. 2009; 157–161p.

Yu H, Li M, Zhang HJ et al. Color texture moments for content-based image retrieval. In Image Processing. 2002; 3: 929–932p.

Arthi K, Vijayaraghavan MJ. Content based image retrieval algorithm using colour models. International Journal of Advanced Research in Computer and Communication Engineering. 2013; 2(3): 1343–1347p.

Kekre HB, Sonawane K. Histogram partitioning for feature vector dimension reduction in bins approach for CBIR. IJECCE. 2012; 3(6): 1630–1639p.

Downloads

Published

2015-12-17

Issue

Vol. 2 No. 3 (2015)

Section

Research Articles

License

Declaration and Copyright Transfer Form

(to be completed by authors)

I/ We, the undersigned author(s) of the submitted manuscript, hereby declare, that the above manuscript which is submitted for publication in the STM Journals(s), is not published already in part or whole (except in the form of abstract) in any journal or magazine for private or public circulation, and, is not under consideration of publication elsewhere.

  • I/We will not withdraw the manuscript after 1 week of submission as I have read the Author Guidelines and will adhere to the guidelines.
  • I/We Author(s ) have niether given nor will give this manuscript elsewhere for publishing after submitting in STM Journal(s).
  • I/ We have read the original version of the manuscript and am/ are responsible for the thought contents embodied in it. The work dealt in the manuscript is my/ our own, and my/ our individual contribution to this work is significant enough to qualify for authorship.
  •  I/We also agree to the authorship of the article in the following order:

Author’s name                                    

 

1. ________________

2. ________________

3. ________________

4. ________________

 

We  Author(s) tick this box and would request you to consider it as our signature as we agree to the terms of this Copyright Notice, which will apply to this submission if and when it is published by this journal.