摘要
本文在二叉判别树的基础上,提出了一种新的多级假设检验的两级图象匹配方法。给出了表示多级假设检验的二叉判别树的定义及计算代价公式,导出了一种新的可变门限,得出了采用可变门限的多级假设检验的两级图象匹配的计算代价。计算机模拟实验表明,本文提出的方法能突破两级模板匹配计算代价的极限,降低图象匹配的计算代价,同时保证了接近于平均绝对差算法的匹配定位精度。
A new method of two-stage image matching with multiple assumption tests based on two-fork deciding tree is proposed in this paper. First, the definition of twofork deciding tree representing multiple assumption tests and its computational cost formula are given. Then, a new variable threshold is derived. Finally, the computational cost of two-stage image matching with multiple assumption tests using variable threshold is obtained. A large amount of computer simulations shows that the limit of computational cost of original twostage template matching can be broken by the proposed method and the computational cost of image matching is further reduced. Furthermore, it is sure that the matching location accuracy is almost the same as the Mean Absolute Difference Algorithm.
出处
《电子学报》
EI
CAS
CSCD
北大核心
1989年第2期103-105,共3页
Acta Electronica Sinica
