Multimedia Databases

The Basic Steps for multimedia indexing is :

1. Provide a measure for the distance between two multimedia objects :
   So we need to define a distance function D().Given two objects OA, OB the distance (=dis-similarity) of the two objects is denoted by D(OA, OB). It can be Euclidean Distance .
2. Similarity Queries :
   • Whole query matches : for a query of object O , find the objects within the database which are with in similarity distance delta from O.
     
   • Sub-pattern Match : Given a collection of N objects O1,…, ON and a query (sub-) object Q and a tolerance delta identify the parts of the data objects that match the query Q .
   • Or we can find k nearest neigbours of object queried.
3. Algorithm : Sequential scanning and distance calculation with each and every object is too slow for large databases. We can use highly fine-tuned database SAMs (Spatial Access Methods) like R-trees to accelerate the search (by pruning out large portions of the database that are not promising) .

The similarity distance can be based on features extracted from image. Like in previous post for an image the similarity can be based on color, texture etc