SURVEY ON CONTENT-BASED IMAGE RETRIEVAL (CBIR) SYSTEM

JAGATHKRISHNA TS; Pranav S Plavida; Jugal Krishna; Nandana VA; Saveo PS; Reeny zackarias; Sanam E Anto

SURVEY ON CONTENT-BASED IMAGE RETRIEVAL (CBIR) SYSTEM

April 2025

Vol-11, Issue-2

Paper ID: 26349

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Engineering

Keywords

content-based image retrieval (CBIR) Feature Extraction Deep Learning Convolutional Neural Networks (CNNs) Semantic Gap Similarity Matching Image Indexing Locality-Sensitive Hashing (LSH) FAISS Computational Complexity Real-Time Image Retrieval Scalable Search Systems.

Abstract

Content-Based Image Retrieval (CBIR) has emerged as a prominent method of effective image retrieval based on visual image features, i.e., shape, texture, and color, rather than text-based information. Traditional CBIR systems are plagued by issues such as the semantic gap between low-level image features and high-level human perception, computationally expensive operations in handling large amounts of data, and ineffectiveness in real-time performance. Recent advances in deep learning, particularly Convolutional Neural Networks (CNNs), have revolutionized CBIR by promising more accurate and scalable feature extraction. The present survey paper reviews a range of CBIR methods from traditional feature extraction methods to deep-learning-based techniques. The paper also presents similarity matching methods, indexing methods, and system architectures that enable retrieval efficiency. Further, the paper presents ongoing challenges confronting CBIR and future research directions, namely, cloud-based deployments, AI-based personalized searching, and enhanced security features. These advances are resulting in robust, intelligent, and scalable image retrieval systems that can discover widespread applications across a broad range of applications ranging from healthcare to security to e-commerce

License

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

Author Information

#	Name	Institute / Affiliation
1	JAGATHKRISHNA TS	Holy Grace Academy of Engineering
2	Pranav S Plavida	Holy Grace Academy of Engineering
3	Jugal Krishna	Holy Grace Academy of Engineering
4	Nandana VA	Holy Grace Academy of Engineering
5	Saveo PS	Holy Grace Academy of Engineering
6	Reeny zackarias	Holy Grace Academy of Engineering
7	Sanam E Anto	Holy Grace Academy of Engineering

How to Cite

Use the following formats to cite this article in your research.

APA Style

TS, JAGATHKRISHNA, Plavida, Pranav S, Krishna, Jugal, VA, Nandana, PS, Saveo, zackarias, Reeny, & Anto, Sanam E (2025). SURVEY ON CONTENT-BASED IMAGE RETRIEVAL (CBIR) SYSTEM. International Journal of Advance Research and Innovative Ideas In Education, 11(2), 2926-2938.

MLA Style

TS, JAGATHKRISHNA, et al. "SURVEY ON CONTENT-BASED IMAGE RETRIEVAL (CBIR) SYSTEM." International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 2, 2025, pp. 2926-2938.

IEEE Style

JAGATHKRISHNA TS, Pranav S Plavida, Jugal Krishna, Nandana VA, Saveo PS, Reeny zackarias, and Sanam E Anto, "SURVEY ON CONTENT-BASED IMAGE RETRIEVAL (CBIR) SYSTEM," International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 2, pp. 2926-2938, 2025.

Vancouver Style

TS JAGATHKRISHNA, Plavida Pranav S, Krishna Jugal, VA Nandana, PS Saveo, zackarias Reeny, et al. SURVEY ON CONTENT-BASED IMAGE RETRIEVAL (CBIR) SYSTEM. International Journal of Advance Research and Innovative Ideas In Education. 2025;11(2):2926-2938.

Harvard Style

TS, JAGATHKRISHNA, Plavida, Pranav S, Krishna, Jugal, VA, Nandana, PS, Saveo, zackarias, Reeny, & Anto, Sanam E (2025) 'SURVEY ON CONTENT-BASED IMAGE RETRIEVAL (CBIR) SYSTEM', International Journal of Advance Research and Innovative Ideas In Education, 11(2), pp. 2926-2938.

Chicago Style

TS, JAGATHKRISHNA, et al. "SURVEY ON CONTENT-BASED IMAGE RETRIEVAL (CBIR) SYSTEM." International Journal of Advance Research and Innovative Ideas In Education 11, no. 2 (2025): 2926-2938.

Turabian Style

TS, JAGATHKRISHNA, et al. "SURVEY ON CONTENT-BASED IMAGE RETRIEVAL (CBIR) SYSTEM." International Journal of Advance Research and Innovative Ideas In Education 11, no. 2 (2025): 2926-2938.