Content-based image retrieval

<p>Content-based image retrieval, also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR), is the application of <a href="/facts/Computer_vision/Tl2Yyk66">computer vision</a> techniques to the <a href="/facts/Image_retrieval/pkcq1rTk">image retrieval</a> problem, that is, the problem of searching for <a href="/facts/Digital_image/3TNT47Mv">digital images</a> in large <a href="/facts/Database/VYcpkevb">databases</a> (see this survey for a scientific overview of the CBIR field). Content-based image retrieval is opposed to traditional concept-based approaches (see <a href="/facts/Concept-based_image_indexing/dj1Mp4Fb">Concept-based image indexing</a>).
</p><p>"Content-based" means that the search analyzes the contents of the image rather than the <a href="/facts/Metadata_(computing)/qt35z79C">metadata</a> such as keywords, tags, or descriptions associated with the image. The term "content" in this context might refer to colors, shapes, textures, or any other information that can be derived from the image itself.  CBIR is desirable because searches that rely purely on metadata are dependent on <a href="/facts/Automatic_image_annotation/8V2cAfwG">annotation</a> quality and completeness.
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Content-based image retrieval open-in-new

Content-based image retrieval