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A Binarization Method for a Scenery Image with the Fractal Dimension

机译:分形维数的风景图像二值化方法

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We propose a new binarization method suited for character extraction from a sign board in a scenery image. The binarization is thought to be a significant step in character extraction in order to get high quality result. Character region of 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 bi-narized result is sensitive to the threshold change. 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 stabile against an interval of the threshold value. Focusing attention on this point, we propose a new method which obtains a threshold value based on the fractal dimension to evaluate both region's density and stability to threshold change. Through the proposed method, we can get a fine quality binarized images, where the characters can be extracted correctly.
机译:我们提出了一种新的二值化方法,适用于从风景图像中的招牌中提取字符。为了获得高质量的结果,二值化被认为是字符提取中的重要步骤。然而,叹气板的字符区域具有许多变化和颜色。除此之外,如果在背景中存在诸如山或树的高频纹理区域,则可能导致难以对图像进行二值化。在高频区域,二值化结果对阈值变化敏感。另一方面,标牌的字符区域由实心区域组成,即包括很少的高频区域,并且具有相对高的对比度。因此,字符区域的二值化结果相对于阈值的间隔是稳定的。针对这一点,我们提出了一种新的方法,该方法基于分形维数来获取阈值,以评估区域的密度和阈值变化的稳定性。通过提出的方法,我们可以获得高质量的二值化图像,可以正确提取字符。

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