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基于灰度积分投影的人眼定位
引用本文:冯建强,刘文波,于盛林.基于灰度积分投影的人眼定位[J].计算机仿真,2005,22(4):75-77.
作者姓名:冯建强  刘文波  于盛林
作者单位:南京航空航天大学自动化学院,江苏,南京,210016
摘    要:该文提出了一种基于最大类间方差阈值分割和灰度积分投影技术的眼睛定位方法。首先通过图像预处理技术中的中值滤波方法去除图像噪声,并通过非线性变换消除人脸图像因为曝光条件不同而造成的模糊,得到灰度分配较为均匀的图像,然后利用最大类间方差阈值法对图像进行二值化处理,将特征点从人脸图像分割出来,并分别利用水平和垂直灰度积分投影曲线结合人脸的结构特征找到眼睛的位置坐标,实现了准确的眼睛定位,从而为进一步提取其它特征点打好了基础。

关 键 词:特征提取  眼睛定位  阈值分割  积分投影
文章编号:1006-9348(2005)04-0075-02
修稿时间:2003年10月9日

Eyes Location Based on Gray-level Integration Projection
FENG Jian-qiang,LIU Wen-Bo,YU Sheng-lin.Eyes Location Based on Gray-level Integration Projection[J].Computer Simulation,2005,22(4):75-77.
Authors:FENG Jian-qiang  LIU Wen-Bo  YU Sheng-lin
Abstract:An algorithm for eyes location is presented in this paper based on m ax imum variance between two classes and gray-level integration projection. First, median filter is used to eliminate the noise, then the image blur caused by defi cient exposal is cleared up using non-linear transform. Maximum variance betwee n two classes is provided to get the binary image, and then the features are ext racted from the image. Finally, by the way of gray-level integration projection and human face configuration, we can easily find that the location of eyes is d etermined by the coordinate of the minimum in the diagram. Further feature detec tion can be done based on this result.
Keywords:Feature extraction  Eye location  Threshold segment  Integration projection  
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