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

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

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.