摘要
将图像二值化作为一个优化问题来解决:通过最小化一个加权误差平方和函数来找到最佳阈值·给出了一个快速的迭代优化算法来实现这一目标·还将新方法和一个最经典、常用的二值化方法进行了比较·理论分析和实验结果均表明,两种方法是等价的,但本文对该问题的新的描述,能够推导出一个更加有效的算法·新算法有着更广泛的实际应用,特别是在实时的视频监控与跟踪系统中·
Unlike the usual way to find out automatically a threshold from image histogram, the image binarization is dealt with as an optimization problem where the best threshold could be found out by minimizing a weighted function of error sum of squares, with a fast iterative optimization algorithm given for the purpose. The new approach is compared with a most classic and commonly-used binarization method, and the result shows that the two methods are equivalent in view of either theoretical analysis or experimental data. However, our formulation relevant to the problem enables us to derive up a much more efficient algorithm available to more applications,especially to real-time video monitoring and tracking systems.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2004年第12期1149-1152,共4页
Journal of Northeastern University(Natural Science)
基金
教育部高等学校优秀青年教师教学与科研奖励基金资助项目
关键词
二值化
直方图
优化
分割
阈值
binarization
histogram
optimization
segmentation
threshold
