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2-D minimum fuzzy entropy method of image thresholding based on genetic algorithm

机译:基于遗传算法的图像阈值二维最小模糊熵方法

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摘要

A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the characteristic relationship between the gray level of each pixel and the average value of its neighborhood. When the threshold is not located at the obvious and deep valley ofthe histgram, genetic algorithm is devoted to the problem of selecting the appropriate threshold value. The experimental results indicate that the proposed method has good performance.
机译:引入了一种新的图像阈值化方法,该方法基于二维直方图,并且最大限度地减少了输入图像模糊性的度量。提出了模糊隶属度函数的新定义,它表示每个像素的灰度与其邻域平均值之间的特征关系。当阈值不在直方图的明显和深谷处时,遗传算法致力于选择合适的阈值的问题。实验结果表明,该方法具有良好的性能。

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