对编码结构光采集图像的区域分割  

Area segmentation for coded-light acquired pictures

作　　者：王骁[1] 张爱军[1] 

机构地区：[1]北京化工大学机电工程学院,北京100029

出　　处：《北京化工大学学报（自然科学版）》2015年第1期107-112,共6页Journal of Beijing University of Chemical Technology(Natural Science Edition)

摘　　要：对图像进行阈值有关处理时,局部内容的处理效果会受到图像中其他部分的影响,导致分割效果不佳,且常用的分割方法是针对单一连通域的处理,并不适用于分割由大量连通域构成的形体内容。为了对这样的内容进行分割,本文提出一种基于数理统计原理的分割算法,自动的划分出采集图像中主要内容的部分,并利用两个参数控制轮廓的尺寸和外形。通过实验对比了直接处理和本文方法处理的识别符号数量,结果表明,本文算法将图像中前景区域划分后再针对该区域进行图像处理比直接全图处理的效果更好,提升了符号的识别率。When acquiring symbol-coded structured-light images,the shape of the tested object in the image is formed by masses of symbols. In order to obtain 3D information about the tested object,each symbol should be recognized and to obtain detailed symbol information,a series of image proceedings are needed. When using the threshold process image,the effect of one part will be influenced by the other parts. Therefore the image segmentation is poor. Typical segmentation methods commonly operate in a single connected domain. In order to segment a shape which is composed of masses of domains,a new method based on mathematical statistics has been developed in this work. The method can automatically extract the main content of an image by a contour. The contour size and shape are controlled by two parameters. Through experiment,the method divides the image into two regions and processes the foreground region. The effect of this method is better than direct image processing and it enhances the symbol recognition ratio.

关 键 词：结构光 图像处理 统计算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]