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This paper proposes a hybrid system for text detection in video frames. The system consists of two main stages. In the first stage text regions are detected based on the edge map of the image leading in a high recall rate with minimum computation requirements. In the sequel, a refinement stage uses an SVM classifier trained on features obtained by a new local binary pattern based operator which results in diminishing false alarms. Experimental results show the overall performance of the system that proves the discriminating ability of the proposed feature set.