content based image retrieval (Computers - Software)

USNetAds > Computers > Software

Item ID 131468985 in Category: Computers - Software

content based image retrieval

Takeoff Projects helps students complete their academic projects.You can enrol with friends and receive content based image retrieval kits at your doorstep. You can learn from experts, build latest projects, showcase your project to the world and grab the best jobs. Get started today!
Content-based image retrieval, 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 (see this survey[1] for a scientific overview of the CBIR field). Content-based image retrieval is opposed to traditional concept-based approaches (see Concept-based image indexing).

"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.[2] "Keywords also limit the scope of queries to the set of predetermined criteria." and, "having been set up" are less reliable than using the content itself.[3]

The most common method for comparing two images in content-based image retrieval (typically an example image and an image from the database) is using an image distance measure. An image distance measure compares the similarity of two images in various dimensions such as color, texture, shape, and others. For example, a distance of 0 signifies an exact match with the query, with respect to the dimensions that were considered. As one may intuitively gather, a value greater than 0 indicates various degrees of similarities between the images. Search results then can be sorted based on their distance to the queried image.[14] Many measures of image distance (Similarity Models) have been developed.[19]

Related Link: Click here to visit item owner's website (0 hit)

Target State: All States
Target City : All Cities
Last Update : Jul 26, 2021 8:27 AM
Number of Views: 80
Item  Owner  : keerthana pothula
Contact Email: (None)
Contact Phone: (None)

Friendly reminder: Click here to read some tips.
USNetAds > Computers > Software
 © 2022
2022-05-17 (0.400 sec)