摘要
鉴于现有的形态学梯度边缘检测算子没有考虑梯度的矢量性,在边缘检测部分提出了具有方向估计的形态学梯度算子,并将平滑处理加入该系列算子,使这些算子在噪声抑制和提高边缘清晰度两方面均有较好的表现。同时,在图像分割部分运用了多层次自适应的模糊阈值分割方法,利用自适应的方法对典型的模糊分割器的窗宽进行调整,并运用多层次的局部调整使图像分割后的物体边缘更加完整清晰。
This paper provides a edge segmentation arithmetic based on gradient vector. At first, it has a arithmetic having orientation estimate morphological gradient edge detection operators. There are four element structures with different direction. In these operators, the blurring processing is added, it makes that the operators not only depress the noise in image, but also enhance edge＇s definition. Second, in the segmentation, it includes a new adaptive threshold based on fuzziness which makes edge more intact and clearer.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2006年第6期484-488,共5页
Geomatics and Information Science of Wuhan University
基金
中国人民解放军总装备部"十五计划"资助项目
关键词
方向估计
平滑
矢量
结构元素
自适应阈值分割
orientation estimate
blurring
threshold fuzziness vector variable
structure element
adaptive
