The automatic text detection in document images is useful for many applications. This paper presents an algorithm that can automatically detect and extract text in digital document images. Firstly, we process and fuse Gabor filtered images at different orientations and scales and obtain an image that reflects the layout of the document image. Then, potential text regions are directly extracted from the resulting image. Finally, two criteria based on the geometrical property and high frequency content are adopted to kick-out those non-text regions. The experiments are performed on some representative images with different styles and with texts in different languages and fonts. Experimental results show that the algorithm works well on document images from a wide variety of source.