Survey on Content-Based Image Retrieval System : Fundamentals and Parameters

Authors

  • Uttamjeet Kaur  CSE, SBBSU, Punjab, India

Keywords:

CBIR, Color, Shape, Texture, Classification, Feature vector, Similarity measure, Performance parameters.

Abstract

CBIR (Content-based image retrieval) is a challenging method of capturing related images from large storage spaces. Although this field has been explored for decades, there is no technology that can achieve the accuracy of human visual perception when distinguishing images. Regardless of the size and content of the image database, humans can easily identify images of the same category. From the very beginning of CBIR to study textures, colors and shapes are considered to be the original visual cues of the image. T Although image retrieval using texture features is not a completely new approach, there is still a range of improved retrieval accuracy by appropriately representing texture features. This paper studies the basic concepts of content-based image retrieval systems. This survey attempts to introduce the theory and practical application of CBIR technology.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-10-30

Issue

Volume 3, Issue 7, September-October-2018

Section

Research Articles

License

Copyright (c) IJSRCSEIT

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Uttamjeet Kaur, " Survey on Content-Based Image Retrieval System : Fundamentals and Parameters, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 7, pp.276-281, September-October-2018.