GRECO中棱边判别算法的改进

Improvement in Edges Detecting Method in GRECO

图形电磁计算方法(GRECO)是解决电大尺寸目标高频电磁散射的有效方法之一,而对模型的棱边判别是该方法中的关键步骤。针对传统方法无法判断模型边缘是否为棱边的缺陷,利用自然图像边缘检测算法完成边缘像素的提取,再将模型适当旋转获取隐藏面像素法矢,得到边缘劈角角度,从而排除边缘像素中非棱边像素。同时,文章提出了一种自适应的阈值设定方法,使算法对不同的模型均具有良好的自适应性。计算实例表明,该方法具有较高的准确性和计算效率。

Graphical electromagnetic computing method （GRECO） is one of the efficient methods to solve the problem of high-frequency electromagnetic scattering of electronically large size targets. The detection of the model edge is a key step in the method. There is a defect in traditional method that it could not determine whether the fringe pixels of the model are edge pixels. In this paper, the natural image edge detection algorithm is used to extract fringe pixels. Then the model is rotated to get the normal of hidden surface pixels and the edge angle, to exclude the non-edge pixels in fringe pixels. Meanwhile, a setting method based on adaptive threshold is proposed to achieve better adapt- ability for different models. Calculation examples show that the proposed method has higher accuracy and efficiency.