新的MR-CT图像轮廓提取方法

New contour extracting method of MR-CT images

提出了一种新的轮廓提取算法,并将这种算法应用到MR-CT图像的轮廓提取。该算法首先计算图像的灰度阈值,选定属性形态运算递增准则中的属性,并构造选定属性的直方图,通过灰度阈值得到在属性直方图对应的属性阈值;对图像进行属性形态开闭运算,将图像多余信息滤除,再应用典型梯度算子中的罗伯特算子得到图像对象轮廓。证明了该算法具有递增性、幂等性、反扩展性和移不变性。对这种方法在MR-CT图像上进行了实验,实验结果表明MR-CT轮廓能完好地提取出来。仿真实验还证明:该方法有效地保留图像的必要信息,同时具有强抗噪性而且轮廓边缘保持完好。

A new contour extraction method was presented and applied in MR-CT images to get the contours. The new contour extraction method got the gray threshold firstly. The attribute of image in the criteria of attribute operation was constructed. The selected attribute histogram was structured. The attribute threshold was gotten by the corresponding gray threshold in the attribute histogram. The images were operated by the attribute open and close operation. The useless information in image was removed. Then Roberts operator of classical gradient operators was used to get the image contour. Some important properties such as increment, idempotency, anti-extension and displacement invariability were proposed and proved. This method was experimented on MR-CT images. The results show that the contours of MR-CT images were obtained satisfactorily. The simulating experimental results show that the method getting attribute threshold automatically can retain the important information of image effectively. The new contour extraction method has the strong anti-noise ability and the shapes of contours are kept good.