![]() These keywords can be found in the title of the video, text accompanying the video or can be defined by the author. Usually the results come with a miniature capture of the video.Ĭurrently, almost all video searchers are based on keywords (search by metadata) to perform searches. Some searchers also enable to use as search parameters the format or the length of the video. Some video searchers process the search directly in the Internet, while others shelter the videos from which the search is done. There are image searchers that combine both search techniques, as the first search is done by entering a text, and then, from the images obtained can refine the search using as search parameters the images which appear as a result.Ī video search engine is a search engine designed to search video on the net. This system requires a higher computational complexity, but is more efficient and reliable than search by metadata. During the search it is examined the content of the image such as color, shape, texture or any visual information that can be extracted from the image. Search by example: In this technique, also called reverse image search, the search results are obtained through the comparison between images using content-based image retrieval computer vision techniques. This metadata generation process is called audiovisual indexing. and can be generated manually or automatically. The metadata associated with each image can reference the title of the image, format, color, etc. and it is obtained a set of images sorted by relevance. Search by metadata: Image search is based on comparison of metadata associated with the image as keywords, text, etc. Two techniques currently used in image search: The results depend on the search criterion, such as metadata, distribution of color, shape, etc., and the search technique which the browser uses.ĭiagram of a search realized through example based on detectable regions from an image Image search techniques The search can be based on keywords, a picture, or a web link to a picture. Visual information searchers Screenshot of results shown by the image searcher through example GOS Image search Īn image search engine is a search engine that is designed to find an image. Scale-invariant feature transform - to extract local features of an image.Discover webpages where the image appears.Ĭommonly used reverse image search algorithms include:.These search engines often use techniques for Content Based Image Retrieval.Ī visual search engine searches images, patterns based on an algorithm which it could recognize and gives relative information based on the selective or apply pattern match technique. Examples are buildings in a foreign city. This type of search engines is mostly used to search on the mobile Internet through an image of an unknown object (unknown search query). Information may consist of web pages, locations, other images and other types of documents. ![]() ![]() ![]() Ī visual search engine is a search engine designed to search for information on the World Wide Web through a reverse image search. Reverse image search also allows users to discover content that is related to a specific sample image, popularity of an image, and discover manipulated versions and derivative works. This effectively removes the need for a user to guess at keywords or terms that may or may not return a correct result. In particular, reverse image search is characterized by a lack of search terms. Reverse image search is a 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 very useful in its ways. Content-based image retrieval Reverse image search using Google Images. ![]()
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