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.
Figure. An example of Image retrieval operation
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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