一种新的基于改进弹簧质点模型的图像边缘检测方法*

针对传统边缘检测算法不能准确定位图像的边缘和检测出的图像边缘连续性较差的不足，在基于改进 的弹簧质点模型基础上提出一种新的、简单和有效的图像边缘检测算法。在该算法中，将被检测的像素点作为中心点，其周围八个方向的像素点对该中心点的弹簧拉力组成一个平面内的弹簧质点模型。根据胡克定律，可以计算出作用在中心点上的合力大小，如果作用在中心点上合力大小超过设定的阈值， 则认为该中心点为边缘上的点。实验结果表明，提出的算法能够有效地克服传统算法的不足，而且具有一定的噪声滤波效果。

Novel approach for edge detection based on improved spring-mass model

As the continuity of the image edge is poor and the edge could not be located exactly when we use traditional edge detection algorithms, this paper presents a new, simple and effective edge detection approach based on improved spring-mass model. In this paper, the detected point is considered as a center such that the spring-pulling forces from the eight neighboring pixels form a spring-mass model in a plane.According to Hooke Law, we can calculate magnitude of the sums of all spring tension acted on the center point, the center point can be considered as an edge point if magnitude of the sums is greater than certain threshold. The experimental results show that the proposed algorithm can effectively overcome shortages of traditional edge detection methods, further more, the proposed algorithm has certain noise suppression.