摘要
针对Canny算子在阈值偏高或偏低的情况下会产生边缘丢失或伪边缘的缺陷,提出了一种基于细菌觅食算法与改进最大类间方差法(Otsu算法)相结合的自适应阈值Canny算子。根据图像的梯度幅值直方图将像素点进行分类,并基于改进的Otsu算法定义描述类间方差的适应度函数,通过细菌觅食算法自动获取使适应度函数最优的高低阈值。实验结果表明,该方法在目标边缘提取的准确性上优于传统算法。
In order to fix the defects of broken edges or fake edges while the thresholds are too high or too low in original Canny algorithm, this paper proposes a new algorithm for Canny edge extraction with adaptive thresholds based on Bacte-rial Foraging Optimization algorithm（BFA）and enhanced Otsu algorithm. According to the value of gradient amplitude histogram, pixels are divided into edge type, non-edge type and pending type;A fitness function is defined to describe the mean square error among the three pixel type based on the enhanced Otsu algorithm;Both of the low and high thresholds are selected with the process of BFA. The experimental results show that this method is more accurate than original methods in edge extraction.
出处
《计算机工程与应用》
CSCD
2014年第4期161-165,共5页
Computer Engineering and Applications
基金
中央高校基本科研业务费专项资金资助(No.GK201002028
No.GK201101001)
陕西师范大学研究生创新基金资(No.2013CXS042)
