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Combined-with-Canny

于 2020-07-01 发布 文件大小:205KB
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   对经典的二值化方法Ostu 算法和Bernsen 算法中存在的缺点进行了分析, 提出一种结合Canny 算子的图像 二值化方法.该方法综合考虑了边缘信息和灰度信息, 通过边缘附近种子点在高阈值二值化图像中的填充和低阈值 图像对它的修补而得到二值化结果图像, 较好地解决了经典二值化方法中存在的抗噪能力差、边缘粗糙、伪影现象 等缺点.实验结果证明, 该方法能够较好地解决低对比度图像和目标像素灰度不均匀图像的二值化问题(The disadvantage of the classical binary method Ostu Bernsen algorithm and algorithms exist were analyzed, one binding Canny operator image binarization method. This method considers the edge information and gray information, through seed near the edge point padding and a low threshold image to its repair in a high threshold binary image to obtain a binary result image, it solves the noise immunity classical binary method exists difference, rough edges, artifacts phenomenon and other shortcomings. the experimental results show that this method can solve the low-contrast image and the target image pixel gray uneven binary problem)

文件列表:

结合Canny算子的图像二值化_陈强.pdf,226703,2016-10-22

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