数学形态学在数字图像处理中的应用研究
投稿时间:2020-09-02  修订日期:2020-11-10  点此下载全文
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宋冬梅 西北大学现代学院 710130 asffww124@sina.com 
中文摘要:传统边缘检测算法由于对噪声敏感,难以准确提取图像边缘,导致图像处理效果不佳。本文基于传统数学形态学算法中结构算子的方向性和尺寸几何的基础上进行算法改进。针对抗噪型碰撞腐蚀形态学边缘检测算子结构元素特征,采用不同大小结构元素组合来提取边缘特征,有效保证了图像细节的同时去掉较大噪声点。根据结构元素的方向性,利用同向结构元素图像的匹配来检测各边缘信息,确保不同向边缘信息的完整度。通过比较文本改进算法与传统的边缘检测算法对图像边缘检测效果表明:本文提出的改进算子在处理较大图像边缘检测是具有更快的检测速度,且图像边缘光滑,细节清晰,具备了更强的抗噪性能。
中文关键词:数学形态学  边缘检测  结构元素  抗噪性
 
Application of Mathematical Morphologyin Digital Image Processing
Abstract:Absrtact: because of its sensitivity to noise, the traditional edge detection algorithm is difficult to extract image edges accurately, which leads to poor image processing effect. Based on the directionality and dimensional geometry of structural operators in traditional mathematical morphology algorithm, the algorithm is improved. Aiming at the feature of edge detection operator of anti-noise collision corrosion morphology, the combination of different size structure elements is used to extract edge features, which effectively ensures the image details and removes the larger noise points at the same time. According to the directionality of the structural elements, the matching of the image of the same structural elements is used to detect the edge information and ensure the integrity of the different edge information. Improved by comparing text The effect of the algorithm and the traditional edge detection algorithm on image edge detection shows that the improved operator proposed in this paper has faster detection speed in processing larger image edge detection, and the image edge is smooth and the details are clear. It has stronger anti-noise performance.
keywords:mathematical morphology  edge detection  structural elements  noise resistance
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