A New Binarization Method for a Sign Board Image with the Blanket Method
Hiromi Yoshida, Naoki Tanaka · 2009
We propose a new binarization method suited for character extraction from a sign board in a scenery image. The binarization is one of a significant step in character extraction in order to get high quality result. Character region on sigh board, however, has many variation and colors. In addition to it, if there exists high frequency texture region like a mountain or trees in the background, it can be a cause of difficulty to binarize an image. At the high frequency region, the binarized result is sensitive to the threshold value. On the other hand, a character region of sign board consists of solid area, that is, includes few high frequency regions, and has relatively high contrast. So the binarized result of character region is stable at an interval of the threshold value. Focusing attention on this point, we propose a new binarization method which obtains a threshold value based on the fractal dimension by evaluating both region's density and stability to threshold value. Through the proposed method, we can get a fine quality binarized images, where the characters can be extracted correctly.