Content-Based Image Retrieval by Integration of Metadata Encoded Multimedia Features in Constructing a Video Summarizer Application.
Description: Content-based image retrieval (CBIR) is the retrieval of images from a collection by means of internal feature measures of the information content of the images. In CBIR systems, text media is usually used only to retrieve exemplar images for further searching by image feature content. This research work describes a new method for integrating multimedia text and image content features to increase the retrieval performance of the system. I am exploring the content-based features of an image extracted from a video to build a storyboard for search retrieval of images. Metadata encoded multimedia features include extracting primitive features like color, shape and text from an image. Histograms are built for all the features extracted and stored in a database. Images are searched based on comparing these histogram values of the extracted image with the stored values. These histogram values are used for extraction of keyframes from a collection of images parsed from a video file. Individual shots of images are extracted from a video clip and run through processes that extract the features and build the histogram values. A keyframe extraction algorithm is run to get the keyframes from the collection of images to build a storyboard of images. In video retrieval, speech recognition and other multimedia encoding could help improve the CBIR indexing technique and makes keyframe extraction and searching effective. Research in area of embedding sound and other multimedia could enhance effective video retrieval.
Date: May 2003
Creator: Anusuri, Ramprasad
Partner: UNT Libraries