CONTENT BASED IMAGE RETRIEVAL
"Content-based" means that the
search analyzes the contents of the image rather than the metadata 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 annotation
quality and completeness. Having humans manually annotate images by entering
keywords or metadata in a large database can be time consuming and may not
capture the keywords desired to describe the image. The evaluation of the
effectiveness of keyword image search is subjective and has not been
well-defined. In the same regard, CBIR systems have similar challenges in
defining success.
Content-based image retrieval (CBIR),
also known as query by image content (QBIC) 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.
Content-based image retrieval is opposed to traditional concept-based
approaches
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