欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
数字式射线图像（DR图像）缺陷检测主要是进行缺陷区域的分割和测量,分割精度将直接影响到测量精度。C-V模型是一种新的基于曲线演化理论和水平集方法的图像分割模型,它结合区域信息使得分割结果全局最优,可以很自然地处理轮廓线拓扑结构的变化。针对工件DR图像特点,研究了一种DR图像缺陷检测的C-V方法：首先应用C-V模型进行DR图像缺陷区域的分割,在此基础上,完成缺陷区域几何参数的测量。实验表明,C-V方法能准确地分割出DR图像中的缺陷区域,并获得缺陷形心和面积等参数。
英文摘要：
The primary work of defect detection of Digital Radiography（DR） image is the segmentation and measurement of defect regions.The precision of defect measurement,to a large extent,depends on the accuracy of segmentation.Based on the curve evolution theory and level set method for segmentation,C-V model has taken regional information into account so that a globally optimal solution can be got,on the other hand,this model also can naturally handle contour topology changes.Aiming at the traits of DR image,this paper researches on a C-V method of defects detection in DR image.In the method, firstly,C-V model is applied to defects segmentation for DR image,on this basis,defects measurement is achieved.The experiment shows that the C-V method can accurately divide defect regions of DR image,and get its geometric parameters.
同期刊论文项目
同项目期刊论文
The construction of 2D rotationally invariant wavelets and their application in image edge detection
期刊信息
位置：