北京交通大学学报2013，Vol.37Issue(2)：27-30,4.
基于多尺度空间PCNN模型的图像分割算法
Image segmentation algorithm based on pulse coupled neural networks of multi-scale space
摘要
Abstract
The license plate of the moving vehicle image has some characteristics such as small proportion, random positions and different sizes. The plate regions are easily in a state of under-segmentation and over-segmentation when we segment the vehicle images. Pulse coupled neural network(PCNN) is known as the third generation neural network and is widely used in image segmentation. In the process of image segmentation which uses pulse coupled neural networks to simulate human vision, traditional PCNN model can't meet the scale change needs for image segmentation because of the fixed values in the connection weight matrix. In order to solve this problem, the method of image segmentation based on pulse coupled neural networks of multi-scale space was proposed. The scale space was introduced into traditional PCNN model to make the model possess the scale characteristics and improve the system' s ability to segment license plate image adaptively.关键词
图像分割/脉冲耦合神经网络模型/尺度空间/多尺度空间PCNN模型Key words
image segmentation/ pulse coupled neural networks model/ scale space/ multi-scale space PCNN model分类
信息技术与安全科学引用本文复制引用
杨娜,陈后金,郝晓莉,李艳凤..基于多尺度空间PCNN模型的图像分割算法[J].北京交通大学学报,2013,37(2):27-30,4.基金项目
国家自然科学基金资助项目(61271305,61201363) （61271305,61201363）
