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  2. MrSID - Wikipedia

    en.wikipedia.org/wiki/MrSID

    MrSID (pronounced Mister Sid) is an acronym that stands for multiresolution seamless image database.It is a file format (filename extension.sid) developed and patented [2] [3] by LizardTech (in October 2018 absorbed into Extensis) [4] for encoding of georeferenced raster graphics, such as orthophotos.

  3. PhotoDNA - Wikipedia

    en.wikipedia.org/wiki/PhotoDNA

    The UK Internet Watch Foundation, which has been compiling a reference database of PhotoDNA signatures, reportedly had over 300,000 hashes of known child sexual exploitation materials. [ citation needed ] Another source of the database was the National Center for Missing & Exploited Children (NCMEC).

  4. Image retrieval - Wikipedia

    en.wikipedia.org/wiki/Image_retrieval

    An image retrieval system is a computer system used for browsing, searching and retrieving images from a large database of digital images. Most traditional and common methods of image retrieval utilize some method of adding metadata such as captioning, keywords, title or descriptions to the images so that retrieval can be performed over the annotation words.

  5. ImageNet - Wikipedia

    en.wikipedia.org/wiki/ImageNet

    The ImageNet project is a large visual database designed for use in visual object recognition software research. More than 14 million [1] [2] images have been hand-annotated by the project to indicate what objects are pictured and in at least one million of the images, bounding boxes are also provided. [3]

  6. Reverse image search - Wikipedia

    en.wikipedia.org/wiki/Reverse_image_search

    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.

  7. Content-based image retrieval - Wikipedia

    en.wikipedia.org/wiki/Content-based_image_retrieval

    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).