摘要
在全面分析Pal.King模糊边缘检测算法的基础上,针对已有算法存在的缺陷,提出了一种改进的模糊边缘检测算法。该算法给出了利用遗传算法确定最佳隶属度阈值的方法,采用简单的隶属函数,简化了Pal.King复杂的变换和逆变换,根据需要对μc进行优化处理,较快获取理想效果,将"Max"和"Min"算子结合起来提取图像边缘。仿真结果表明,采用改进的方法边缘检测质量得到了很大改善,运算速度得到了显著提高。
On the basis of comprehensive analysis about limitations of Pal.King algorithm,an improved algorithm of fuzzy edge-detection is presented.Also proposed is a new method based on genetic algorithm to determine the optimal threshold of the membership grade.The simple membership function proposed in the paper simplifies the complex transformation calculation in Pal.King algorithm.In order to obtain the desired effect,the μc value is optimized according to the requirement.The edges of the image are extracted according to a rule combining the ＂Max＂ and ＂Min＂ operators.Simulation results show that with the proposed algorithm the quality of edge detection is largely improved and the computation of the algorithm is faster than that of Pal.King algorithm.
出处
《激光与红外》
CAS
CSCD
北大核心
2010年第12期1374-1377,共4页
Laser & Infrared
关键词
边缘检测
模糊
阈值分割
隶属度函数
edge-detection
fuzzy
segmentation threshold
membership function
