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.

@article{171941,
        author = {Dr. Harsh Mathur and Mr. Sanjay Pal},
        title = {A Review of Genetic Algorithm-Based Optimization in Content-Based Image Retrieval},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {1339-1343},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=171941},
        abstract = {Content-Based Image Retrieval (CBIR) is a critical area of research in the field of computer vision and multimedia information retrieval. The use of genetic algorithms (GAs) for optimizing CBIR systems has gained significant attention due to their ability to explore complex search spaces efficiently. This review paper summarizes existing literature on CBIR systems, emphasizing the challenges of feature selection, dimensionality reduction, and computational efficiency. Furthermore, it examines the application of GAs for optimizing feature set processing in CBIR, highlighting their advantages, limitations, and potential future directions.},
        keywords = {},
        month = {January},
        }