摘要
大多数由像素灰度值或灰度相关参数获得图像轮廓线的方法由于受到图像噪声、量化误差以及灰阶的梯度分布等方面的影响 ,获得的边缘轮廓线是不光滑的 ,带有小而密集的不规则锯齿或毛刺 ,这不仅不符合实际情况 ,而且会给进一步的图像处理带来困难。为了获得连续光滑的轮廓线 ,提出了一种方法 :先以动态规划算法提取全局最优的轮廓线 ,然后用一种自适应三次B样条对获得的轮廓线进行修饰和平滑处理。该样条可根据轮廓线不同处的曲率变化情况 ,自适应地调整控制点的分布。在各类图像上的试验表明 ,该方法即有效的消除了轮廓线上的小锯齿 。
Image segmentation is an important process in computer vision Most of the currently popular methods tracking the object edge depend on pixel gray value Because of the noise in images and the pixel resolving, the detected contours are far from smoothness and with many tiny zigzags, which will affect the subsequent processing A novel method was put to get smooth contour in image segmentation process Firstly, adopt dynamic programming algorithm to process the object image and to get a global optimal boundary, then smoothing and fitting the boundary by adaptive B spline, which adjusts the control points depending on the contour curvature Practical numerical experimental results show that this method has stronger edge detection ability and produced smoother contour curve than other methods and without losing edge feature at the same time
出处
《光学技术》
CAS
CSCD
2001年第5期477-480,共4页
Optical Technique
关键词
轮廓提取
图像分割
样条
自适应
contour detection
image segmentation
B spline
adaptive
