Analysis of select Reverse Image Search Engines as reflected in Alpha Brand Media

Authors

Keywords:

Reverse Image Search Engine, Image Reuse, Image Similarity, Visual Search, Multimedia Verification

Abstract

This paper presents a comparative analysis of popular reverse image search engines such as Google, TinEye and Yandex focusing on their functionalities, strengths, and capabilities in various applications. Reverse image search engines enable users to find identical or similar images without relying on text-based queries, facilitating efficient visual content retrieval. This study highlights the diverse applications of reverse image search, including copyright protection, visual content recognition analysis, combating misinformation and etc. The study also examines the indexing capabilities, metadata retrieval, and performance of each engine in different contexts, ultimately showcasing the unique strengths of each Reverse Image Search Engine. The results of the study indicates that Google, for example, leads in superior language and text detection and is the only engine to index both home and internal pages of websites, as well as social media images, which is a critical feature for protecting intellectual property. Tineye, on the other hand, excels in showing the first upload date and image metadata, helping in authenticity verification.

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Author Biographies

  • Dr. Gururaj S. Hadagali, Karnatak University, Dharwad

    Professor, Department of Library and Information Science, Karnatak University, Dharwad—580 003, Karnataka State, INDIA, Email: gururajhadagali123@gmail.com, Cell: +91 99452 11029, ORCID iD: 0000-0003-1372-4721

  • Mr. Vishwa N. Naikar, Karnatak University, Dharwad

    Mr. Vishwa N. Naikar

    Department of Library and Information Science

    Karnatak University, Dharwad - 580 003

    Email: vishwa.n.naikar@gmail.com

    Mobile No.: +91 8105270479

References

Choe, J., Choi, H. Y., Lee, S. M., Oh, S. Y., Hwang, H. J., Kim, N., & Seo, J. B. (2024). Evaluation of retrieval accuracy and visual similarity in content-based image retrieval of chest CT for obstructive lung disease. Scientific Reports, 14(1), 4587.

DOI:10.1038/s41598-024-54954-5

Dang, V., Nguyen, T. S., Tran, M. T., & Dang-Nguyen, D. T. (2024, May). Detecting Misinformation in Photos Utilizing Reverse Image Search. In Proceedings of the 2024 International Conference on Multimedia Retrieval (pp. 1321-1323).

DOI:10.1145/3652583.3658420

Hanaa Al-Lohibi, Tahani A., Assagran, M., & Amal. (2020). Awjedni: A Reverse-Image-Search. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, (9), 49-68. DOI:10.14201/ADCAIJ2020934968

Kelly, E. J. (2015). Reverse Image Lookup of a Small Academic Library Digital Collection. Codex: The Journal of the Louisiana Chapter of the ACRL, 80-92. http://journal.acrlla.org/index.php/codex/article/view/101

Late, E., Ruotsalainen, H., & Kumpulainen, S. (2023). In a perfect world: exploring the desires and realities for digitized historical image archives. Proceedings of the Association for Information Science and Technology, 60(1), 244-254.

https://doi.org/10.1002/pra2.785

Lynn, N. C., & Aung, S. S. (2015). Review on Reverse Image Search Engines and Retrieval Techniques (Doctoral dissertation, MERAL Portal).

https://www.academia.edu/92395838/Review_on_Reverse_Image_Search_Engines_and Retrieval_Techniques

Palreddy, A., Bhupta, M. A., Neha, K., & Reddy, R. C. (2023). Reverse Image Lookup System. Journal of Survey in Fisheries Sciences, 10(1).

https://sifisheriessciences.com/index.php/journal/article/view/1225/632

Mathisen, B. (2025). Art history, computer vision… and the face of Abraham Lincoln. Electronic Imaging, 37, 1-13.

DOI: 10.2352/EI.2025.37.11.HVEI-215

Khan, S. A., Dierickx, L., Furuly, J. G., Vold, H. B., Tahseen, R., Linden, C. G., & Dang‐Nguyen, D. T. (2025). Debunking war information disorder: A case study in assessing the use of multimedia verification tools. Journal of the Association for Information Science and Technology, 76(5), 752-769.

DOI: https://doi.org/10.1002/asi.24970

He, Q., Umair, M., Bouguettaya, A., & Abusafia, A. (2025). Determining modified versions of social media images. World Wide Web, 28(3), 1-49.

DOI: https://doi.org/10.1007/s11280-025-01335-1

Pritchard, K., Williams, H. C., & Miller, M. C. (2025). Methodological reflections on tracing networked images. Qualitative Research in Organizations and Management: An International Journal, 20(1), 28-43.

DOI: 10.1108/QROM-08-2024-2801

Published

2026-09-30

Issue

Section

Articles

How to Cite

Analysis of select Reverse Image Search Engines as reflected in Alpha Brand Media (A. Dundannanavar, G. . Hadagali, & V. Naikar, Trans.). (2026). Journal of Indian Library Association, 62(3), 328-336. https://journal.ilaindia.net/index.php/lib/article/view/902

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