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In this paper, a new hybrid method for text detection in natural scene is proposed. According the linguistics rules, this algorithm mainly consists of three parts. First, considering both unary property and binary relationship, the conditional random field (CRF) model is introduced for text region detection. Second, connected components (CCs) are extracted by similar stroke width, and filtered coarsely by stroke width analysis. Candidate CCs are then filtered by candidate regions. Finally, text CCs are clustered into words by geometry heuristics. Experiments on the public benchmark ICDAR 2003 dataset show that proposed algorithm can detect text with various font sizes in natural scene.