焊缝缺陷的水淹没分割算法  

Segmentation of Weld Defects Based on Water-Flooding Principle

作　　者：申清明[1] 高建民[1] 李成[1] 

机构地区：[1]西安交通大学机械制造系统工程国家重点实验室,西安710049

出　　处：《西安交通大学学报》2010年第3期90-94,共5页Journal of Xi'an Jiaotong University

基　　金：国家"863计划"资助项目(2006AA04Z441)

摘　　要：针对焊缝射线检测图像缺陷分割速度慢、精度低的问题,提出了一种基于水淹没原理的缺陷分割算法,即依据水流借势取径、盈满则溢的思想,对缺陷及周边区域进行逐级淹没,并根据淹没面积变化来确定分割阈值.该算法首先利用灰度曲线波形分析检测缺陷,获取缺陷种子点,然后从种子点出发对图像进行逐级淹没,淹没过程采用逐线搜索策略.淹没结束后,通过分析各水位淹没面积相对增量的变化来确定阈值水位.实验结果表明,水淹没分割算法的分割耗时大约是Alaknanda方法的5.3%,Kaftandjian方法的25%,分割误差大约是Alaknanda方法的27.33%,Kaftandjian方法的53.14%,因此具有较好的分割速度和精度.To improve the rate and accuracy of weld defect segmentation in radiographic images,a segmentation method based on water-flooding principle is proposed.According to the principle water flows downwards to the low-lying-land and runs over when it is full,the region of a defect and its neighbor are flooded and the threshold value is determined in terms of the growth of the flooded area.The waveform analysis of gray level profiles is used to detect a defect and get the seed point.Then,a flooding process is carried out starting from the seed point,where a line by line search strategy is employed.Once flooding,the threshold is determined by analyzing the relative increment of the flooded area.The experimental results show that the computation cost of the proposed method is 5.3% and 25% of that of Alaknanda method and Kaftandjian method,and the segmentation error gets 27.33% and 53.14%.

关 键 词：射线检测图像 缺陷分割 水淹没 逐线搜索策略 

分 类 号：TN911.7[电子电信—通信与信息系统]