Dominant Color and Texture Approached for Content Based Video Images Retrieval

Abstract

Content-based retrieval allows finding information by searching its content rather than its attributes. Content-based search and retrieval of video data becomes a challenging and important problem. Every year video content is growing in volume and there are different techniques available to capture, compress, display, store and transmit video while editing and manipulating video based on their content is still a non-trivial activity. Recent advances in multimedia technologies allow the capture and storage of video data with relatively inexpensive computers. However, without appropriate search techniques all these data are hardly usable. Today research is focused on video retrieval.Moreover, content-based video retrieval system requires first of all segment the video stream into separate shots. Video Shot Afterwards features are extracted for video shots representation. And finally, choose a similarity/distance metric and an algorithm that is efficient enough to retrieve query - related videos results. There are two main issues in this process; the first is how to determine the best way for video segmentation and key frame selection. The second is the features used for video representation. Various features can be extracted for this sake including either low or high level features. A key issue is how to bridge the gap between low and high level features. In this paper we presented approach for content based video retrieval based on Dominant color and texture of a video image. We also talk about video Representation, feature extraction from like texture, dominant color and color histogram from video frame. Keywords- Video retrieval, dominant color, Gray level co occurrence matrix. Feature extraction, Key frame extraction, Video representation, and Video segmentation. Image Retrieval, color Histogram