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In this paper, we describe an approach to extract text from broadcast videos. Candidate blocks are detected based on edge extraction results. Corners and geometrical features are used for the purpose of initial classification which is carried out by using a support vector machine (SVM). Considering the spatial inter-dependencies of different regions in the image, we propose a novel conditional random field (CRF) based framework which integrates the outputs of SVM into the system to improve the accuracy of labeling for blocks. The experimental results show that the proposed system achieves reliable performance for text detection/extraction from videos.