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Title: :  SURVEY ON CONTENT-BASED IMAGE RETRIEVAL (CBIR) SYSTEM
PaperId: :  26349
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 11 Issue 2 2025
DUI:    16.0415/IJARIIE-26349
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
JAGATHKRISHNA TSHoly Grace Academy of Engineering
Pranav S PlavidaHoly Grace Academy of Engineering
Jugal KrishnaHoly Grace Academy of Engineering
Nandana VAHoly Grace Academy of Engineering
Saveo PSHoly Grace Academy of Engineering
Reeny zackariasHoly Grace Academy of Engineering
Sanam E AntoHoly Grace Academy of Engineering

Abstract

Computer Engineering
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.
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

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IJARIIE 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 Volume 11 Issue 2 2025 Page 2926-2938
MLA 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 11.2(2025) : 2926-2938.
APA JAGATHKRISHNA TS, Pranav S Plavida, Jugal Krishna, Nandana VA, Saveo PS, Reeny zackarias, & Sanam E Anto. (2025). SURVEY ON CONTENT-BASED IMAGE RETRIEVAL (CBIR) SYSTEM. International Journal Of Advance Research And Innovative Ideas In Education, 11(2), 2926-2938.
Chicago 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 11, no. 2 (2025) : 2926-2938.
Oxford 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, 2025, p. 2926-2938. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/SURVEY_ON_CONTENT_BASED_IMAGE_RETRIEVAL__CBIR__SYSTEM_ijariie26349.pdf (Accessed : ).
Harvard JAGATHKRISHNA TS, Pranav S Plavida, Jugal Krishna, Nandana VA, Saveo PS, Reeny zackarias, and Sanam E Anto. (2025) 'SURVEY ON CONTENT-BASED IMAGE RETRIEVAL (CBIR) SYSTEM', International Journal Of Advance Research And Innovative Ideas In Education, 11(2), pp. 2926-2938IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/SURVEY_ON_CONTENT_BASED_IMAGE_RETRIEVAL__CBIR__SYSTEM_ijariie26349.pdf (Accessed : )
IEEE 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, Mar-App 2025. [Online]. Available: https://ijariie.com/AdminUploadPdf/SURVEY_ON_CONTENT_BASED_IMAGE_RETRIEVAL__CBIR__SYSTEM_ijariie26349.pdf [Accessed : ].
Turabian 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 [Online]. volume 11 number 2 ().
Vancouver 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 [Internet]. 2025 [Cited : ]; 11(2) : 2926-2938. Available from: https://ijariie.com/AdminUploadPdf/SURVEY_ON_CONTENT_BASED_IMAGE_RETRIEVAL__CBIR__SYSTEM_ijariie26349.pdf
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