摘要
主要应用基于MIC角点检测的snake模型进行图像分割研究。传统的snake算法只考虑曲线本身的特征,并没有充分的利用被拟合图像本身的特征,而此算法首先检测被拟和目标的角点,然后以这些角点为基准进行曲线初始化,最后根据snake算法进行目标拟和;较好地解决了传统snake模型对初始化位置敏感、对有角点和凹陷的图像收敛效果差的缺点。实验表明此算法达到了很好的效果。
The image segmentation is studied according the snake model based on the comer. The traditional snake model only applies the features of the curve, which did not adequately apply the feature of the image. But in the algorithm, the comers of the detected object is detected based on the MIC operator; the initialized curve is set based on the comers; the object is fitted according on the snake model. The traditional snake model highly depended on the initialized position of the curve and can not get well fitted effort for the image which has the corners and concaves. The proposed algorithm preferably solve the drawbacks. The experiment proves that the algorithm has very good segmentation efforts.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第16期30-32,共3页
Computer Engineering and Applications
基金
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60603092)
关键词
角点检测
图像分割
蛇算法
corner detection
image segmentation
snake model
