一种改善的基于支持向量机的图像边缘检测算法

摘要

本文给出一种基于支持向量机方法的边缘检测算法,用以改善传统边缘检测方法中存在的比如粗糙边缘、不准确边缘等缺点.支持向量机是建立在统计学理论基础上的一种新的机器学习方法.首先提出了边缘检测算法流程,然后使用支持向量机分类方法对图像进行边缘检测.用所得到的边缘检测算法与Prewitt算法的性能进行了比较.仿真结果表明本文给出的算法与Prewitt算法相比,边缘检测性能得到提高.%Considering the disadvantages in the traditional image edge detection methods, such as rough edge and inaccurate edge location, an improved image edge detection algorithm method based on support vector machine ( SVM ) is proposed. SVM is a new method of machine learning. It is based on the statistical learning theory. Algorithm flow is proposed firstly, and then performs the detection using the SVM classification. The performance of the presented edge detection algorithm is compared with Prewitt detectors. The experimental result demonstrates that the effect of the edge detection is greatly improved comparing with Prewitt edge detection methods.