摘要
为了快速得到图像分割的最佳阈值,依据图论知识,利用灰度级相似矩阵代替像素级权值矩阵,将归一化切割准则作为优化函数.利用粒子群优化算法代替穷举法优化归一化划分准则,提出粒子群算法优化归一割的图像阈值分割方法.实验表明在分割性能上有较大的提高,在分割速度上也有较大的改进,能够满足实时性要求.
In order to get the optimal threshold in image segmentation quickly,based on the graph theory,gray-scale similar matrix takes the place of pixel-level weight matrix,normalized cut criterion is regarded as the optimization function.Using particle swarm optimization algorithm to find the best threshold in gray-scale space.Experiments show that the method is not only less computational costs,but also get a satisfactory segmentation result.The thresholds is more stable and consume less time greatly and better satisfies the request of real-time processing in image segmentation by using this new method.
出处
《西安工程大学学报》
CAS
2012年第3期337-341,共5页
Journal of Xi’an Polytechnic University
基金
陕西省教育厅科研计划项目(11JK0506)
宝鸡文理学院科研计划项目(YK1026)
关键词
阈值分割
归一化割
粒子群算法
图像分割
threshold segmentation
normalized cut
particle swarm algorithm
image segmentation
