Text supply crucial suggestions for understanding video content, also the information that the text convey is much more concise than corresponding audio or video. The reason is that we need language knowledge to understand the text, and the knowledge itself does not need to be embedded in the text data. Text streams contain very rich semantic information. How to effectively extract information from text is an important component in video content analysis and semantics research. In this paper, a new morphology-based method for text detection in image and video is proposed. It consists of three major stages. In the first stage, the input color image is converted to gray-scale, a morphological binary map is generated by calculating the difference between the closing image and the opening image, and a binarization is performed. In the second stage, candidate regions are connected by using a morphological dilation and erosion operations. In the last stage, the extracted regions are verified based on characteristic of text regions to eliminate non text regions.

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