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Video shot boundary detection is one of the fundamental tasks of video indexing and retrieval applications. Although many methods have been proposed for this task, finding a general and robust shot boundary method that is able to handle the various transition types caused by photo flashes, rapid camera movement and object movement is still challenging. We present a novel approach for detecting video shot boundaries in which we cast the problem of shot boundary detection into the problem of text segmentation in natural language processing. This is possible by assuming that each frame is a word and then the shot boundaries are treated as text segment boundaries (e.g. topics). The text segmentation based approaches in natural language processing can be used. The experimental results from various long video sequences have proved the effectiveness of our approach.