Effective CBIR System Using Color Histogram and Distance Measures

Authors

  • Punit Soni
  • Vijay Kumar Lamba
  • Surender Jangra
  • Sunil Kumar

DOI:

https://doi.org/10.37591/jowet.v6i1.2077

Abstract

Abstract

Interests to precisely retrieve desired images from databases of medical images are developing every day. Certain features define the images; on the basis of those, the retrieval of images is facilitated. These components incorporate texture, color, shape and region. A lot of work has been done in this direction to discover the new ways to use these features in image retrieval process. In this study, we exhibit an overview of the Content Based Image Retrieval (CBIR) methods taking into account texture, color, and shape. In this study, we present a color histogram-based image retrieval system that can retrieve the images by direct image features matching with query image features by using distance classification. Content based access to digital medical images for supporting decision making has been suggested that would facilitate the administration of clinical information and situations. We have actualized new feature extraction based image retrieval and advanced feature extraction methods. For image retrieval, we have utilized color histogram function to extract the features and on the basis of extracted features matching of query image as divergence measure. Proposed retrieval strategy is far better than the conventional techniques that use picture to picture coordinating which builds the time taken in the recovery process. In this work, a complete system of image retrieval which is perfectly balanced in efficiency and efficacy is explored. As compared to previous procedures, we got higher values of precision, recall and F-score. In future, more efficient training methods could also be merged into the study.

Keywords: Feature extraction, histogram, image retrieval, precision

Cite this Article

Punit Soni, Vijay Kumar Lamba, Surender Jangra, et al. Effective CBIR System Using Color Histogram and Distance Measures. Journal of Web Engineering & Technology. 2019; 6(1): 11–14p.

Downloads

Published

2019-05-14

Issue

Vol. 6 No. 1 (2019)

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.