Reverse image search

Reverse image search using Google Images.

Reverse image search is content-based image retrieval (CBIR) query technique that involves providing the CBIR system with a sample image that it will then base its search upon; in terms of information retrieval, the sample image is what formulates a search query. In particular, reverse image search is characterized by a lack of search terms. This effectively removes the need for a user to guess at keywords or terms that may or may not return a correct result. Reverse image search also allows users to discover content that is related to a specific sample image,^[1] popularity of an image, and discover manipulated versions and derivative works.^[2][3]

Uses

Reverse image search may be used to:^[4][5]

• Locate the source of an image
• Find higher resolution versions
• Discover webpages where the image appears
• Track down the content creator
• Get information about an image

Algorithms

Commonly used reverse image search algorithms include:^[6]

• Scale-invariant feature transform - to extract local features of an image ^[7]
• Maximally stable extremal regions
• Vocabulary Tree

Production Reverse Image Search Systems

• Google Images
• Tineye
• ImageWiki
• Other systems: MyPicGuard,Image Raider, Multi-Service image search, Yandex Images, Karma Decay.^[8]
• Reverse Image Search Windows Phone App powered by Google, Bing, Tineye and Yandex

Application in Popular Search Systems

Google Images

Google Images

Google's Search by Image is a feature that utilizes reverse image search and allows users to search for related images just by uploading an image or image URL. Google accomplishes this by analyzing the submitted picture and constructing a mathematical model of it using advanced algorithms.^[9] It is then compared with billions of other images in Google's databases before returning matching and similar results. It should be noted that when available, Google also uses meta-data about the image such as description

TinEye

TinEye

TinEye is a search engine specializing in reverse image search. Upon submitting an image, TinEye creates a "unique and compact digital signature or fingerprint" of said image and matches it with other indexed images.^[10] This procedure is able to match even heavily edited versions of the submitted image, but will not usually return similar images in the results.^[11]

For all applications of content-based image retrieval, see List of CBIR engines.

References