基于GPN径向基神经网络的边缘检测方法  

Edge Detection Method Based on GPN Radial Basis Neural Network

作　　者：刘洋 杨晟院[1] 钟雅瑾[2] LIU Yang;YANG Shen-Yuan;ZHONG Ya-Jin(College of Information Engineering,Xiangtan University,Xiangtan 411105,China;School of Software and Information Engineering,Hunan Software Vocational Institute,Xiangtan 411100,China)

机构地区：[1]湘潭大学信息工程学院,湘潭411105 [2]湖南软件职业学院软件与信息工程学院,湘潭411100

出　　处：《计算机系统应用》2020年第3期140-147,共8页Computer Systems & Applications

基　　金：国家自然科学基金(11571293)。

摘　　要：在基于神经网络的边缘检测模型中,大部分模型的检测效率不高,检测效果也有待提升.本文受人眼视觉系统特性的启发,提出了一种新的基于GPN(Gaussian Positive-Negative)径向基神经网络的边缘检测方法.首先,本文构造了一种新型的基于GPN径向基神经网络,将图像中经高斯滤波预处理后的每个像素点作为GPN径向基神经网络的中心点,并将其输入神经网络;然后,在每层之间使用卷积神经网络的部分特性进行处理,经过扩展层和隐层计算后输出结果;最后根据输出结果利用轮廓跟踪的方法将边缘提取出来.本文在检测效果以及效率这2个方面进行了相应的数值实验.针对合成图像以及部分灰度不均匀图像,相较于脉冲耦合神经网络模型、遗传神经网络模型以及卷积神经网络模型,本文模型在效率上得到了提升,且边缘的连通性更好.实验结果表明,本文提出的基于GPN径向基神经网络的边缘检测方法是一种新的、有效的边缘检测方法,比传统的神经网络边缘检测方法效率更高,且在检测效果上也有所提升.In the edge detection model based on neural network,most of models have lower detection efficiency,and the detection effect needs to be improved.Inspired by the characteristics of biological vision systems,a new edge detection method based on Gaussian Positive-Negative(GPN)radial basis neural network is proposed in this study.Firstly,we construct a new GPN radial-based neural network,which takes each pixel point preprocessed by Gaussian filtering in the image as the center point of the GPN radial-based neural network and inputs it into the neural network.Then,the partial characteristics of the convolutional neural network are used between each layer for processing,and the results are output after the expansion layer and the hidden layer are calculated.Finally,the edges are extracted by the contour tracking method according to the output result.In this study,the corresponding numerical experiments are carried out in two aspects:detection effect and efficiency.For the composite images and some intensity inhomogeneous images,compared with the pulse-coupled neural network model,the genetic neural network model and the convolutional neural network model,the proposed model is improved in efficiency and the edge connectivity is better.The experimental results show that the proposed edge detection method based on GPN radial basis neural network is a new and effective edge detection method,which is more efficient than the traditional neural network edge detection method,and the detection effect is also improved.

关 键 词：径向基神经网络 卷积神经网络 轮廓跟踪 边缘检测 人眼视觉系统 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP183[自动化与计算机技术—计算机科学与技术]