Analytical Classification of Multimedia Index Structures by Using a Partitioning Method-Based Framework

Computer Science – Multimedia

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

Due to the advances in hardware technology and increase in production of multimedia data in many applications, during the last decades, multimedia databases have become increasingly important. Contentbased multimedia retrieval is one of an important research area in the field of multimedia databases. Lots of research on this field has led to proposition of different kinds of index structures to support fast and efficient similarity search to retrieve multimedia data from these databases. Due to variety and plenty of proposed index structures, we suggest a systematic framework based on partitioning method used in these structures to classify multimedia index structures, and then we evaluated these structures based on important functional measures. We hope this proposed framework will lead to empirical and technical comparison of multimedia index structures and development of more efficient structures at future.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Analytical Classification of Multimedia Index Structures by Using a Partitioning Method-Based Framework does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Analytical Classification of Multimedia Index Structures by Using a Partitioning Method-Based Framework, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Analytical Classification of Multimedia Index Structures by Using a Partitioning Method-Based Framework will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-279546

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.