Video Image Detector: A Tool for Finding Similarity in Video Contents
Nowadays, when a sheer volume of multimedia data is being generated on daily basis, video piracy has become a genuine issue. In this paper, we propose a technique for matching video frames in two (or more) video files. Most of the work in this domain has been done on object detection, text detection, and spatio-temporal methods, however, the detection of copyright contents in videos has not been well-addressed. In this paper, we propose a technique to detect the copyright video frames in two or more videos. The given videos can be an advertisement or an especially worked-out video file by a journalist which is legally owned by the person who made it. Such a video files/clips can be matched with certain video streams or files to check if they contain the whole or a part of the given video file. The given video clip is composed of individual frames which could be matched on frame-to-frame basis with other (live) video streams to find the similarity extent between the successive images/frames. The method/technique to be proposed in this project will be mainly helpful for tracking or identifying the copyright digital video contents (e.g., songs, ads, news, etc) being played/transmitted illegally by a digital channel.