摘要
本文提出了一种基于广义模糊性质集的图像分割方法,它利用图像的广义隶属函数,把图像灰度转换成广义的模糊集合,通过对图像作多次增强而实现图像分割。实验结果表明,本文提出的方法与Otsu法、熵函数法和FCM2D法相比,在分割速度和分割质量上,都有不同程度的提高。
In this paper, a new method for image segmentation based on the generalized fuzzy set is presented. By utilizing the generalized membership function,gray scales of image are transformed into the generalized fuzzy set, and then through image enhancement in several times, image segmentation is carried out.Compared with the Otsu method, the entropic function method and the FCM2D method, the experimental results show that the improvements can be achieved to a great extent by using this method in terms of both computation time and image quality.
出处
《计算机应用与软件》
CSCD
1999年第2期52-56,共5页
Computer Applications and Software
关键词
广义模糊集
图像分割
二值化
噪声
图像处理
Generalized fuzzy set, image segmentation, smoothing, binarization, noice.
