New Content Analysis Methods Effective in Multimedia Based Services

In this paper we present new content analysis methods effective in multimedia based services. The problem of multimedia content delivery and retrieval has become more and more important due to the growing amount of video information that is delivered to consumers today. The classical searching and retrieval mode in multimedia databases is by name; however the name cannot truly describe the semantic content of most video content. The solution for this problem is visual content extraction. This means that the multimedia content will be characterized not only by name but also by the most representative information contained. This information is known as visual feature and there are any methods that try to extract visual features from multimedia streams. The methods presented in this paper are based on colour and spatial information and are used for extracting patterns from images and videos. The process of multimedia content retrieval consists of three stages: semantic video modelling, video segmentation and feature extraction. The result of semantic video modelling is the representation of raw data in a more structured form, and it is essential in the following stage. Video segmentation means the partition of an image into a set of non overlapping homogenous regions whose union is the entire image. The presented segmentation methods used are edge-based, region-based and motion-based, and are used for moving or static object detection.