模糊技术能够很好地表达和处理不确定问题，是图像处理领域中一种非常重要的技术。基于模糊理论，文中提出了基于模糊熵的自适应多阈值分割方法。根据图像像素的概率分布，将图像行区域化，利用每个区域中像素属于前景和背景的模糊性定义隶属度函数，采用一维搜索方法确定最佳的隶属度函数窗宽，计算最大模糊熵，从而找到区域最优阈值。文中对多目标、光照不均匀、存在噪声和分割不完全的图像进行实验，结果表明该方法能够很好地解决上述问题，并且较传统的基于Otsu和模糊熵的图像单阈值分割方法，效果显著提高，具有较好的适应性和实用性。%Fuzzy technology,which can well express and deal with uncertain problems,is very important and useful in the field of image processing. Based on the fuzzy theory,an Adaptive Multi-threshold Method (AMM-FE) of image segmentation based on fuzzy entropy is proposed. According to the distribution probability of the image pixels,divide the image into a plurality of regions. Define the member-ship functions using the pixels belonging to the foreground and the background blur in each area,determine the window width of fuzzy membership function by using one-dimension search method,calculating the maximum fuzzy entropy to get the regional optimal thresh-old. By using multi-objective,non-uniform illumination,presence of noise and imperfect image in the experiment,the results show that this method can greatly overcome these incomplete segmentation situations. Compared with traditional single threshold image segmenta-tion methods like Otsu and fuzzy entropy,the effect of this method is significantly improved,which indicates that the proposed AMM-FE method has better adaptability and practicality.
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