The availability of a tremendous amount of videos on Internet nowadays raises a research question of how to automatically classify and label the videos in terms of their contents so as to allow people a quick access based on a particular interest in the types and characteristics of the videos. Organizing video clips into proper categories will make the process of content-based search on large number of videos much faster and improve the accessibility. Also an ability to detect and identify the originality and the creator (author/source) according to the unique shooting characteristics of the videos will be useful in certain applications. A profile created by extracting the features of shot transitions at which the contents of video frames exhibit special patterns of changes helps categorizing videos in different types. The research of this paper experimented on three types of videos (News, Sports, and Music) to show that a content profile built on a new set of frame transition parameters and corresponding statistical measurements could be applied to reveal the specific characteristics and distinguish the different types of videos.