An Efficient CNN-Based Method for Content-Based Image Retrieval

Authors

  • A Mukul Kumar Patro  School of Computer Science and IT, Jain University, Bangalore, Karnataka, India
  • Dr. J Bhuvana  School of Computer Science and IT, Jain University, Bangalore, Karnataka, India

DOI:

https://doi.org//10.32628/CSEIT239024

Keywords:

CBIR, Image Processing, Feature Extraction, Image Retrieval

Abstract

Image recovery has been one of the most fascinating and active study fields in the field of computer vision. The use of content-based image retrieval (CBIR) systems allows for the automatic indexing, searching, retrieval, and exploration of picture datasets. Important characteristics in content-based picture retrieval systems include colour - texture elements. As a result, content-based image retrieval (CBIR) is attractive as a source of precise and speedy retrieval in the modern era. The (CBIR) system uses a feature-based approach to retrieve images from image databases. Low grade characteristics and high grade characteristics are the two categories that image features fall under. Low level aspects of an image include colour, texture, and shape, whereas high level features define the image's semantic content. CBIR is a rapidly developing technology, and as datasets grow as a result of recent advancements in multimedia, it is crucial to enhance this technology to suit user needs.

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Published

2023-04-30

Issue

Section

Research Articles

How to Cite

[1]
A Mukul Kumar Patro, Dr. J Bhuvana, " An Efficient CNN-Based Method for Content-Based Image Retrieval , IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 2, pp.72-77, March-April-2023. Available at doi : https://doi.org/10.32628/CSEIT239024