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The study of binarization algorithm about digital rubbings image based on threshold segmentation and morphology

机译:基于阈值分割和形态学的数字讨论图像二值化算法研究

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摘要

This paper discusses the binarization restoration algorithms of ancient Chinese Rubbings image. According to the location of the image features, such as color, edge, stroke width and pixel location feature, the binary restoration algorithm of digital rubbings based on threshold segmentation and morphology is discussed. If the difference between the text and the background is larger and more obvious distinguish in images, Otsu threshold segmentation method can be directly used. For images with more background noise, shadows and uneven illumination, threshold segmentation cannot achieve effective segmentation and reasonable denoising, a set of algorithms associated with the pixel position of adaptive segmentation, morphological method, connected domain and mean filtering combined of binarization restoration are needed. The experimental results show that this algorithm is very effective for image with complex and large area noise.
机译:本文讨论了古代摩擦图像的二值化恢复算法。根据图像特征的位置,例如颜色,边缘,行程宽度和像素位置特征,讨论了基于阈值分割和形态的数字讨论的二进制恢复算法。如果文本和背景之间的差异更大且更明显地区分图像,则可以直接使用OTSU阈值分割方法。对于具有更多背景噪声的图像,阴影和不均匀照明,阈值分割不能达到有效的分割和合理的去噪,需要与自适应分割,形态学方法,连接域和平均滤波的平均过滤组相关联的一组算法。实验结果表明,该算法对于具有复杂和大面积噪声的图像非常有效。

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