最小邻域均值投影函数及其在眼睛定位算法.提出一种投影函数：最小邻域均值投影函数．该函数通过计算每条投影线上各像素点邻域均值的最小值

来跟踪图像中的低灰度特征．与传统的积分投影函数和方差投影函数相比，它以求最小值的局部选择性代替传统投

影函数的全局累加性，因此具有对片状噪声不敏感的特点、此外，在计算过程中，它还能记录最小值点的二维位置信

息，是一个二维的搜索算子、最小邻域均值投影函数的这些特点使其非常适合于眼睛定位．它对眼睛，特别是瞳孔，总

能够产生精确、鲁棒的响应通过在CAS—PEAL数据库和BioID数据库上的实验表明，其定位正确率与精确度均高

于传统的投影函数．-A projection function called minimal neighborhood mean projection function(MNMPF)is proposed．

The projection function calculates and stores the minimal neighborhood mea1]of each pixel on each projection line，

SO that it is able to trace the low grayscale features in image．Compared with traditional projection functions，i．e．

integral projection function(IPF)and variance projection function(VPF)，MNMPF is insensitive to sheet noise，due

to the local selectivity of its mimmum operation．During the computation of MNMPF,the image locations of

minima are recorded at the same time．This makes MNMPF a 2D operator．All these properties of MNM PF are very

suitable for eye location．It can bring precise and robust response to eyes，especially pupils．Experiments on

CAS—PEAL and BioID databases show its excellent correct rate and precision over traditional projection functions．