使用模糊度量的图像阈值

IECON '98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.98CH36200) Pub Date : 1998-08-31 DOI:10.1109/IECON.1998.722837

N. Yumusak, F. Temurtas, O. Cerezci, S. Pazar

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引用次数: 7

摘要

在图像分析中，将目标与背景分离的图像阈值分割是最常见的应用之一。为了对图像进行预处理，阈值分割是一种必要的工具。本文提出了一种基于最小化模糊测度的新方法。图像中的每个像素和平均图像都有一个隶属度值。利用这些隶属度值计算图像集和平均图像集的模糊熵测度。然后，通过最优最小化计算量来确定阈值。实验结果表明，新方法具有较好的性能，但平均时间较长。

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Image thresholding using measures of fuzziness

In image analysis, image thresholding which is used for separating the object from the background is one of the most common application. For the preprocessing purposes of an image, thresholding is a necessary tool. Here, a new method based on minimizing measures of fuzziness is presented. Every pixel in the image and the averaged image have a membership value. Using these membership values entropy measures of fuzziness of image set and averaged image set are calculated. Then, threshold is founded by optimally minimizing calculated measures. The experimental results indicated that the new method has good performance but takes a long time in averaging.

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IECON '98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.98CH36200)

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