Content Based Image Retrieval
Content-based image retrieval (CBIR) is a technology that allows users to search for digital images based on their visual content, such as colors, shapes, textures, and other visual features.
Origin of
CBIR: -
The origins of CBIR can be traced
back to the 1970s and 1980s when researchers began exploring ways to
automatically analyze and retrieve images based on their visual properties.
One of the
earliest pioneers of CBIR was “J. C. R. Licklider”, is credited with proposing
the idea of a "man-computer symbiosis" in which humans and computers
would work together to solve problems, including the retrieval of visual
information.
In the
1990s, researchers such as Ramesh Jain, Anil K. Jain, and Takeo Kanade at the
University of California, San Diego, and Shih-Fu Chang at Columbia University
developed early CBIR systems using feature extraction and similarity matching
techniques. Since then, many researchers and companies have continued to
advance CBIR technology, with applications ranging from image search engines to
medical diagnosis and more.
CBIR is Really Useful???
CBIR is commonly used in image search engines and
applications where users can upload an image and the system returns similar
images based on the content of the query image. CBIR is also used in various
applications such as medical imaging, remote sensing, and video surveillance.
·
Digital asset management
·
Medical imaging
·
Crime investigation
·
Art history
Content-based
image retrieval (CBIR) is used by a variety of individuals and industries,
including:
·
Photographers and artists: CBIR can help
photographers and artists to search for and find images that match certain
criteria, such as color, composition, and style.
·
Advertising agencies: CBIR can assist
advertising agencies in finding images that are relevant to their campaigns and
target audiences.
·
E-commerce companies: CBIR can help e-commerce
companies to recommend products to customers based on their search queries and
previous purchases.
·
Medical professionals: CBIR can aid medical professionals
in analyzing medical images and identifying patterns or abnormalities.
·
Law enforcement: CBIR can assist law enforcement
agencies in identifying suspects by comparing images from security cameras,
social media, or other sources.
·
Archivists and historians: CBIR can help
archivists and historians to organize and retrieve historical images and
documents.
·
Social media companies: CBIR can aid social
media companies in automatically detecting and removing inappropriate or
harmful content, such as hate speech or graphic violence.
If you are still not clear about CBIR, need more
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Overall, CBIR can be a powerful tool for a range of
applications where image search and analysis are required. However, it's
important to note that the effectiveness of CBIR can depend on factors such as
the quality of the image database, the features used for retrieval, and the
search algorithms employed.
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