采用两组细胞神经网络实现工业CT图像的分割。一组细胞神经网络用粗分割,得到闽值分割图像,在此基础上用另一组细胞神经网络细分割,得到精细的边缘等信息。修正网络稳定态的定义,以网络伪稳定态作为网络迭代过程的终止条件。应用该方法,以发动机切片CT图像作为实验对象,能取得较好的效果。
Two groups of Cellular Neural Networks (CNN) have been used to segment Industrial Computerized Tomography(ICT) Images.The first group,namely rough image segmentation,has been adopted to obtain thresholding images,then with the adaptation of the second group some more sophisticated segmentation information will be procured,with edges included.This article deals with the Pseudo-steady-state of net,which has been served as the termination condition of the iteration.Experimental results of engineering image series demonstrate the efficiency of the methods presented in the article.