摘要
粗糙集理论是一种新的处理模糊和不确定性问题的软计算方法。图像边缘是一类灰度变化大的连续点的集合。在无噪声干扰的情况下,这一特性是区别边缘与非边缘的一个重要条件。而实际应用中,图像中难免混有部分噪声点,影响了边缘检测的准确性。本文提出基于粗糙集理论的图像边缘检测方法。根据粗糙集理论中的集合近似关系,首先利用灰度变化大的特点,找出可能边缘点集合,然后利用噪声点区别于边缘点的特性,找到噪声点集合,最后,两个集合的差就是最终要求的边缘点。实验结果表明,该方法相比于传统的检测方法,在检测准确度上得到了一定的改善。
Rough set theory is a new soft calculation method which used to process fuzzy and indetermination problems. Edge is a kind of collection that involves big gray-scale changes points. In non-noise jamming' s situation, this is a characteristic that distinguishies the difference between edge and non-edge. But in the practical application, the image unavoidably mixes with some noise which impact accuracy of edge detection. This paper presents an image edge detection theory based on rough sets. According to the set' s similar relatious of rough set, it first finds possible edge point set, using the characteristic of big gray-scale chan- ges. Then, uses the difference between noise and edge to find noise set. Finally, the difference between the two sets is on the verge of final demand points. Experimental results show,compared to traditional methods of edge detection, this method has certain improvement in examination accuracy.
出处
《计算机与现代化》
2009年第10期86-87,91,共3页
Computer and Modernization
关键词
粗糙集
边缘检测
边缘梯度
rough sets
edge detection
edge gradient