A New Text Extraction Method Incorporating Local Information

Text detection and extraction in images with complex background can provide useful information for video annotation and indexing. More attention is paid to text detection for its importance, but text extraction is necessary for the text recognition, and it can test the validity of text detection. In this paper, we conclude text extraction is to segment the image and to remove noises, and then a robust text extraction method incorporating local information is proposed. First, we get the gray image from the original image and reprocess the gray image with edge enhancement. Then a binarization method incorporating local information is used to segment the gray image, by which the text-noises are removed and a binary image is obtained. Finally, the connected component analysis based on the character's density and geometric feature is performed on the binary image, by which background-noises are removed. The preliminary experiments show some promising results.

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