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In this paper, an algorithm for detecting text in images and video frames is proposed. The algorithm contains two steps: initial detection and verification. In the first step, edge feature and morphology operation are employed to locate edge-dense image blocks. Empirically rules are applied on these blocks to get candidate text. In the second step, wavelet-based features are employed to represent the texture property of text. A SVM classifier is used to identify text from the candidate ones. Experiments show that this algorithm has 93.9% detection rate for English text and a 92.4% detection rate for Chinese text. The algorithm is robust to language, font-color and size.