自适应多方向灰度形态学图像边缘检测算法

曹风云; 李东兴; 张华强; 杜钦君; 常晓刚; 马良慧

光学技术, 2016, 42 (3): 234, 网络出版: 2016-06-06

自适应多方向灰度形态学图像边缘检测算法

An algorithm of image edge detection based on adaptive multi-directions gray scale morphology

论文大纲

曹风云 ^1,*李东兴 ¹张华强 ¹杜钦君 ²常晓刚 ¹马良慧 ¹

作者单位

¹ 山东理工大学机械工程学院, 山东淄博 255049

² 山东理工大学电气与电子工程学院, 山东淄博 255049

噪声抑制边缘检测灰度形态学结构元素 noise suppressing edge detection gray scale morphology structural elements

摘要

针对传统的多方向灰度形态学边缘检测算法存在计算量大、效率低的缺点, 提出了一种基于自适应噪声抑制的多方向灰度形态学图像边缘检测算法。根据图像所含噪声的种类, 采用不同尺度的结构元素对图像进行分类滤波, 再根据像素点间灰度值的变化确定边缘方向, 由相应方向的结构元素进行边缘检测。实验结果表明, 与传统的多方向灰度形态学边缘检测算法相比, 检测到的边缘重构相似度和边缘置信度更高, 边缘连续性更强, 且计算量低, 运行效率高。

Abstract

Aiming at the disadvantages of large amount calculation and low efficiency of the traditional multi-directions gray-scale morphology edge detection algorithm, a multi-directions gray-scale morphology edge detection algorithm based on adaptive noise suppressing is proposed. According to the type of noise existing in image, the multi-scale structural elements are applied for filtering to the image. The edge direction is determined according to the change between the pixel gray values. The image edge information is detected by the structural elements in the corresponding direction. Experimental results show that the edge reconstruction similarity, the edge confidence level and the edge continuity are better via this algorithm than the traditional multi-directions gray-scale morphology edge detection version, and the computation amount is decreased and the run efficiency is increased.

参考文献

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曹风云, 李东兴, 张华强, 杜钦君, 常晓刚, 马良慧. 自适应多方向灰度形态学图像边缘检测算法[J]. 光学技术, 2016, 42(3): 234. CAO Fengyun, LI Dongxing, ZHANG Huaqiang, DU Qinjun, CHANG Xiaogang, MA Lianghui. An algorithm of image edge detection based on adaptive multi-directions gray scale morphology[J]. Optical Technique, 2016, 42(3): 234.

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