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Image Threshold Segmentation Algorithm Based on Histogram Statistical Property

机译:基于直方图统计属性的图像阈值分割算法

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The traditional Otsu threshold algorithm is not a good method for processing the real images because of complex shape and unbalanced distribution. To solve this problem, the paper uses the thinking of Otsu's method for reference, introduces a threshold segmentation algorithm based on histogram statistical property. In addition, the paper draws a comparison between the new algorithm and Otsu's algorithm. Experimental results show that the new algorithm can get better segmentation effect than that of Otsu's method when the gray-level distribution of the background follows normal distribution approximatively, and the target region is less than the background region.
机译:传统的OTSU阈值算法由于复杂的形状和不平衡分布而不是处理真实图像的好方法。为了解决这个问题,本文使用了Otsu的参考方法的思考,介绍了基于直方图统计特性的阈值分割算法。此外,该论文还借鉴了新算法与OTSU算法之间的比较。实验结果表明,当近似地,当背景的灰度分布遵循正常分布时,新算法可以获得比OTSU的方法的更好的分割效果,并且目标区域小于背景区域。

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