Triggered by technology innovations, there has been a huge increase in the utilization of video, as one of the most preferred types of media due to its content richness, for many significant applications. To sustain an ongoing rapid growth of video information, there is an emerging demand for a sophisticated content-based video indexing system. This project combines a Video scene change algorithm, with the current text segmentation and summarization techniques to build an automatic news video indexing and retrieval system. Television broadcast news are captured both in Video/Audio with the accompanying subtitles in text format. News stories and identified, extracted from the video, are then tagged which reduces the amount of information into a manageable size. Individual news video clips can be retrieved effectively by a combination of video and text, providing distilled information such as a summarized version of the original text and highlights important key words in the text.