基于形态学和细胞神经网络的边缘检测方法

采用形态学方法提取二值图像的边缘,利用二值形态学与离散细胞神经网络(DT-CNM)的某种天然对应关系,将离散细胞神经网络引入形态学,将形态学运算转化为某种特定模板下的多层离散细胞神经网络,然后对该模板进行优化设计使之转化为单层离散细胞神经网络,降低了运算的复杂度.在此基础上,通过综合灰度图像像素在每个比特位上的边缘检测结果,提出了采用二值形态学提取灰度图像边缘的方法.与传统边缘提取方法Sobel和Log相比较,该方法边缘提取效果良好,收敛迅速.

Edge Detection Based on Morphology and Cellular Neural Network

Morphology is used for edge extraction of binary image.In particular,Discrete-time Cellular Neural Network(DT-CNN) is introduced into binary morphology owing to the natural corresponding relationship between them,and then the morphology operation is transformed into multi-layer DT-CNN under some specific template.Multi-layer DT-CNN is transformed into Monolayer DT-CNN by optimizing design to reduce the complexity of the operation.Therefore,we can extract the edge of gray image by synthesizing the edge detec...