基于小波散射卷积网络的纹理分割方法  

Texture Segmentation Based on Wavelet Scattering Convolution Network

作　　者：吴华娟[1,2] 张明新[2] 郑金龙[2] 

机构地区：[1]西北师范大学计算机科学与工程学院,甘肃兰州730000 [2]常熟理工学院计算机科学与工程学院,江苏常熟215500

出　　处：《微电子学与计算机》2013年第5期31-34,共4页Microelectronics & Computer

基　　金：国家自然科学基金项目(61173130)

摘　　要：针对物体的纹理特征进行图像分割的问题,提出一种基于小波散射卷积网络的纹理分割方法.首先利用小波散射卷积网络提取每个子图像块的散射能量分布特征;然后采用全局阈值处理的Ostu方法,对各层级散射能量特征值矩阵进行分类,得到粗分割结果;最后利用形态学方法消除粗分割中的虚假点,得到细分割结果,从而实现了无监督的纹理分割.实验结果表明,该方法用于纹理图像分割及车牌定位都能获得很好的效果.For image segmentation by texture features of the object,this paper presents a texture segmentation method based on scattering wavelet convolution network.First of all,using scattering wavelet convolution network to extract the scattering energy distribution features of each sub-images,and then using the Ostu global threshold processing method to implement the classification of scattering energy feature matrix at all levels,the coarse segmentation results are given.Finally,to remove spurious spots in the coarse segmented image,applying the method of morphology,thereby achieving unsupervised texture segmentation.Experimental results indicate that high accuracy can be achieved for both texture segmentation and license plate location with the proposed methods.

关 键 词：纹理分割 小波变换 散射算子 散射卷积网络 车牌定位 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]