Content Based Image Retrieval using Dynamic weighted features combination

  • Unique Paper ID: 143584
  • Volume: 2
  • Issue: 12
  • PageNo: 26-32
  • Abstract:
  • Content-based image retrieval (CBIR) is an image retrieval technique used to retrieve images efficiently by using low level features (like texture, shape, color) of those images. It is an efficient retrieval mechanism to retrieve images from the multimedia database. The combination of these low level features give better results than individual feature. In the previous years, the amount of low level features to be retrieved were decided based on manual assumption or heuristic experiments. In this paper, we have focused on features extraction process dynamically and improving the precision value. The weightage of image features (color and Shape) are calculated dynamically and then their combination is used to retrieve more relevant images. Euclidean distance method is used for feature matching. An efficiency of image retrieval is measured by precision value of it.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{143584,
        author = {Brinda N. Joshi and Narendrasinh Limbad},
        title = {Content Based Image Retrieval using Dynamic weighted features combination},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {2},
        number = {12},
        pages = {26-32},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=143584},
        abstract = {Content-based image retrieval (CBIR) is an image retrieval technique used to retrieve images efficiently by using low level features (like texture, shape, color) of those images. It is an efficient retrieval mechanism to retrieve images from the multimedia database. The combination of these low level features give better results than individual feature. In the previous years, the amount of low level features to be retrieved were decided based on manual assumption or heuristic experiments. In this paper, we have focused on features extraction process dynamically and improving the precision value. The weightage of image features (color and Shape) are calculated dynamically and then their combination is used to retrieve more relevant images. Euclidean distance method is used for feature matching. An efficiency of image retrieval is measured by precision value of it.
},
        keywords = {Content based image retrieval, Feature matching, CBIR, weighted features, dynamic feature extraction
},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 2
  • Issue: 12
  • PageNo: 26-32

Content Based Image Retrieval using Dynamic weighted features combination

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