一种新的二维方向直方图熵阈值法

Adiljan Yimit, Yukari Hagihara, T. Miyoshi, Y. Hagihara
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引用次数: 2

摘要

自Pun将熵的概念引入到图像分割中以来,各种熵的方法层出不穷。因此,熵法已成为分割的一个主要类别。Abutaleb等人首先引入了二维熵,并考虑了空间相关性。然而,他们的方法占用了太多的计算时间,无法得到更好的结果。本文利用方向直方图,提出了一种基于二维香农熵的熵阈值分割方法。利用多幅图像,将新方法与Abutaleb方法和Xiao等人提出的二维熵阈值法进行了比较。实验结果证明了该方法在二维熵阈值分割方面的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Two-Dimensional Direction Histogram Based Entropic Thresholding
Since the entropic concept was introduced in image segmentation by Pun, many entropic methods have been developed in rapid succession. Consequently, the entropic approach has become a major category of segmentation. Abutaleb et al. firstly introduced the two-dimensional entropies, taking the spatial correlation into account. However, their method takes up too much computational time to give better results. In this paper, a new entropic thresholding method is proposed based on the two-dimensional Shannon entropies by using the orientation histogram. Utilizing several images, the new method is compared with Abutaleb's method and the two-dimensional entropic thresholding method proposed by Xiao et al. The experimental results demonstrate the effectiveness of the proposed method in aspects of two-dimensional entropic thresholding.
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