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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).
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.
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.
3️⃣ To find unauthorized uses of your photos: When it comes to images, copyrights only go so far—plenty of websites will use a photographer’s work without permission even if it’s illegal ...
In the case of document retrieval, queries can be based on full-text or other content-based indexing. Information retrieval is the science [ 1 ] of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds.
Elasticsearch is a search engine based on Apache Lucene. It provides a distributed, multitenant -capable full-text search engine with an HTTP web interface and schema-free JSON documents. Official clients are available in Java , [ 2 ] .NET [ 3 ] ( C# ), PHP , [ 4 ] Python , [ 5 ] Ruby [ 6 ] and many other languages. [ 7 ]
Most Linux distributions, as collections of software based around the Linux kernel and often around a package management system, provide complete LAMP setups through their packages. According to W3Techs in October 2013, 58.5% of web server market share is shared between Debian and Ubuntu , while RHEL , Fedora and CentOS together shared 37.3%.
Concept-based image indexing, also variably named as "description-based" or "text-based" image indexing/retrieval, refers to retrieval from text-based indexing of images that may employ keywords, subject headings, captions, or natural language text (Chen & Rasmussen, 1999). It is opposed to Content-based image retrieval. Indexing is a technique ...