Image thresholding using ultrafuzziness optimization based on type II fuzzy sets

A. Arifin, Aidila Fitri Heddyanna, H. Studiawan
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引用次数: 9

Abstract

Image thresholding is a critical process in digital image processing application. However, there are some disturbing factors like image vagueness and bad illumination resulting in not satisfied image thresholding output. Several fuzzy thresholding techniques are developed to remove graylevel ambiguity during threshold selection. One of the techniques is thresholding method using type II fuzzy sets. In this paper, we propose relaxation of the ultrafuzziness measurement by considering ultrafuzziness for background and object fuzzy sets separately. The proposed method optimizing ultrafuzziness to decrease uncertainty in fuzzy system used type II fuzzy sets. Experimental results on several images show the effectiveness of the proposed method.
基于II型模糊集的超模糊优化图像阈值分割
图像阈值分割是数字图像处理应用中的一个关键环节。但由于图像模糊、光照差等干扰因素,导致图像阈值输出不理想。为了消除阈值选择过程中的灰度模糊性,提出了几种模糊阈值处理技术。其中一种方法是利用II型模糊集的阈值法。在本文中,我们提出了通过分别考虑背景和目标模糊集的超模糊度来放松超模糊度测量的方法。该方法利用二类模糊集对模糊系统的超模糊度进行优化,以降低系统的不确定性。在多幅图像上的实验结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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