摘要
在图像处理中,对于复杂图像的边界特征信息很难通过一个结构元素来提取。针对这一问题,采用多结构元素的图像边界识别算法,利用具有视觉模型的边界阀值选择策略确定图像中梯度变化的像素点,对其采用二值形态学的腐蚀运算,从而判断该像素点是边界点还是噪声点。实验表明此算法具有较好的边界信息提取能力和较好的去噪声能力。
In image processing, it is difficult to withdraw complex image edge characteristic information through a structural element. In response to the problem, a method of the image edge examination based on multiple structuring elements was introduced. By using the choice strategy for edge threshold based on visual perception model, a pixel the gradient varied obviously in the gray-scale image is determined, and it is operated by using erosion of binary morphology to obtain the edge and remove the noise. The experiment results show that this algorithm not only has a good ability to exam the image edge, but also has a strong ability to suppress the noise in the image.
出处
《计算机工程与设计》
CSCD
北大核心
2006年第10期1775-1776,1785,共3页
Computer Engineering and Design
基金
湖南省教育厅科研基金项目(05C719)
关键词
DFBR
数学形态学
结构元素
视觉模型
边界识别
DFBR
mathematical morphology
structuring elements
visual perception model
edge examination
