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An image search engine is a search engine that is designed to find an image. The search can be based on keywords, a picture, or a web link to a picture. The results depend on the search criterion, such as metadata, distribution of color, shape, etc., and the search technique which the browser uses.
The search engine that helps you find exactly what you're looking for. Find the most relevant information, video, images, and answers from all across the Web. Search query
Google Images (previously Google Image Search) is a search engine owned by Google that allows users to search the World Wide Web for images. [1] It was introduced on July 12, 2001, due to a demand for pictures of the green Versace dress of Jennifer Lopez worn in February 2000. [2] [3] [4] In 2011, reverse image search functionality was added.
Reverse lookup is a procedure of using a value to retrieve a unique key in an associative array. [1] Applications of reverse lookup include reverse DNS lookup, which provides the domain name associated with a particular IP address, [2] reverse telephone directory, which provides the name of the entity associated with a particular telephone ...
Visual Image Retrieval and Localization: A visual search engine that, given a query image, retrieves photos depicting the same object or scene under varying viewpoint or lighting conditions. Using Flickr photos of urban scenes, it automatically estimates where a picture is taken, suggests tags, identifies known landmarks or points of interest ...
Image meta search (or image search engine) is a type of search engine specialised on finding pictures, images, animations etc. Like the text search, image search is an information retrieval system designed to help to find information on the Internet and it allows the user to look for images etc. using keywords or search phrases and to receive a set of thumbnail images, sorted by relevancy.
Generating or maintaining a large-scale search engine index represents a significant storage and processing challenge. Many search engines utilize a form of compression to reduce the size of the indices on disk. [20] Consider the following scenario for a full text, Internet search engine. It takes 8 bits (or 1 byte) to store a single character.
General scheme of content-based image retrieval. Content-based image retrieval, also known as query by image content and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases (see this survey [1] for a scientific overview of the CBIR field).