Content-based Image Retrieval: Recent Trends and Techniques


Year : 2025 | Volume : 03 | Issue : 01 | Page : 01-32
    By

    Monika Varshney,

  • Raj Kumar,

  1. Assistant Professor, Department of Computer Science, Dharm Samaj College, Raja Mahendra Pratap Singh University, Aligarh, Uttar Pradesh, India
  2. Assistant Professor, Department of Computer Science, Dr. Bhimrao Ambedkar University, Agra, Uttar Pradesh, India

Abstract

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Due to the affordability of digital devices and the accessibility of internet technologies, a vast number of multimedia databases have been established for various applications. These image databases increase the need for efficient picture retrieval search strategies that meet user requirements. When compared to other systems, the content-based image retrieval (CBIR) system is one of the most widely used systems for retrieving images from enormous databases. Much work has been done in the last few years to enhance CBIR techniques, with an emphasis on closing the semantic gap between high-level and low-level characteristics. Owing to the growing body of research in this area, the present study examines, evaluates, and contrasts, the most advanced techniques currently used in the field of CBIR. This research analyzes the data and gives a summary. It presents new low-level feature extraction techniques, machine learning algorithms, similar metrics, and a comparison of the state-of-the-art techniques’ performance with potential future developments.

Keywords: Content-based image retrieval, feature extraction, color feature, texture feature, shape feature, SIFT, SURF, similarity metrics, machine learning, convolution neural network, SVM

[This article belongs to International Journal of Image Processing and Pattern Recognition (ijippr)]

How to cite this article:
Monika Varshney, Raj Kumar. Content-based Image Retrieval: Recent Trends and Techniques. International Journal of Image Processing and Pattern Recognition. 2025; 03(01):01-32.
How to cite this URL:
Monika Varshney, Raj Kumar. Content-based Image Retrieval: Recent Trends and Techniques. International Journal of Image Processing and Pattern Recognition. 2025; 03(01):01-32. Available from: https://journals.stmjournals.com/ijippr/article=2025/view=0


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Regular Issue Subscription Original Research
Volume 03
Issue 01
Received 30/11/2024
Accepted 16/01/2025
Published 07/02/2025
Publication Time 69 Days
284

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