System Analysis And Design For Multimedia Retrieval Systems

TL;DR

This paper discusses the design of multimedia retrieval systems, emphasizing content-based video retrieval using multiple features like color, texture, edges, and motion to improve search effectiveness in large multimedia collections.

Contribution

It introduces a multimedia retrieval system employing multiple visual features for indexing and retrieval, enhancing video search accuracy.

Findings

Multiple features improve retrieval discrimination.

Content-based indexing enhances search efficiency.

System implementation validates feature effectiveness.

Abstract

Due to the extensive use of information technology and the recent developments in multimedia systems, the amount of multimedia data available to users has increased exponentially. Video is an example of multimedia data as it contains several kinds of data such as text, image, meta-data, visual and audio. Content based video retrieval is an approach for facilitating the searching and browsing of large multimedia collections over WWW. In order to create an effective video retrieval system, visual perception must be taken into account. We conjectured that a technique which employs multiple features for indexing and retrieval would be more effective in the discrimination and search tasks of videos. In order to validate this, content based indexing and retrieval systems were implemented using color histogram, Texture feature (GLCM), edge density and motion..