How similarity search is done in multimedia data? Explain.

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 Similarity Search in Multimedia Data

Since similarities can be searched either on the data description or the data content of multimedia data. For similarity searching in multimedia data, two main families of multimedia indexing and retrieval systems are considered: 

1. Description-based retrieval systems: The system which builds indices and performs object retrieval based on image descriptions, such as keywords, captions, size, and time of creation; description-based retrieval is labor-intensive if performed manually. If automated, the results are typical of poor quality. For example, the assignment of keywords to images can be a tricky and arbitrary task. The recent development of Web-based image clustering and classification methods has improved the quality of description-based Web image retrieval, because image surrounded text information, as well as Web linkage information, can be used to extract proper description and group images describing a similar theme together. 

2. Content-based retrieval systems: The system which supports retrieval based on the image content, such as color histogram, texture, pattern, image topology, and the shape of objects and their layouts and locations within the image. Content-based retrieval uses visual features to index images and promotes object retrieval based on feature similarity, which is highly desirable in many applications. 

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