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Film Line Scratch Detection using a Neural Network based Texture Classifier  

Kim, Kyung-Tai (Dept. of Computer Eng., Konkuk University)
Kim, Eun-Yi (Dept. of Internet and Multimedia Engineering, NITRI, Konkuk Univ.)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.43, no.6, 2006 , pp. 26-33 More about this Journal
Abstract
Film restoration is to detect the location and extent of defected regions from a given movie film, and if present, to reconstruct the lost information of each region. It has gained increasing attention by many researchers, to support multimedia service of high quality. In general, an old film is degraded by dust, scratch, flick, and so on. Among these, the most frequent degradation is the scratch. So far techniques for the scratch restoration have been developed, but they have limited applicability when dealing with all kinds of scratches. To fully support the automatic scratch restoration, the system should be developed that can detect all kinds of scratches from a given frame of old films. This paper presents a neurual network (NN)-based texture classifier that automatically detect all kinds of scratches from frames in old films. To facilitate the detection of various scratch sizes, we use a pyramid of images generated from original frames by having the resolution at three levels. The image at each level is scanned by the NN-based classifier, which divides the input image into scratch regions and non-scratch regions. Then, to reduce the computational cost, the NN-based classifier is only applied to the edge pixels. To assess the validity of the proposed method, the experiments have been performed on old films and animations with all kinds of scratches, then the results show the effectiveness of the proposed method.
Keywords
Film restoration; neural network; film line scratch; scratch detection;
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