基于灰度积分投影与霍夫圆变换算法的人眼瞳距自动检测

Automatic Detection of Human Eye Pupil Distance Based on Gray Integral Projection and Hough Circle Transform Algorithm

人眼瞳距在视光学研究中和配置眼镜时都是需要精确测量的基础性参数,实现瞳距自动检测具有重要的应用价值,结合高斯肤色模型,提出一种基于灰度积分投影与霍夫圆变换算法的人眼瞳孔定位和瞳距计算方法.首先,通过二维伽马函数的自适应亮度校正方法对图像进行光照补偿预处理,在此基础上,利用肤色概率模型检测人脸并提取出面部区域.再运用灰度积分投影法,选取合适的阈值对眼部区域进行提取,经过一系列形态学图像处理,采用Canny边缘检测算子实现瞳孔边缘检测,最后通过Hough圆变换算法进行瞳孔定位,并对其中心距离进行计算.研究结果表明,该算法具有较快的瞳孔定位速度,能够较精确地实现瞳距自动测量,为瞳孔测距的智能化技术研究奠定了基础.

The pupil distance of human eyes is a basic parameter which needs to be measured accurately in optometry research and glasses prescription.It is of great application value to realize automatic pupil distance detection.With the help of a Gaussian skin color model,this study proposes a method of pupil location and pupil distance calculation based on gray integral projection and Hough circle transform.Firstly,the image is subjected to the preprocessing of illumination compensation by the adaptive brightness correction method of a two-dimensional gamma function.On this basis,the face area is extracted by using a skin color probability model.Then,the gray integral projection method is used to extract the eye area by selecting an appropriate threshold.After morphological image processing,the Canny edge detection operator is utilized to detect the pupil edge.Finally,the pupil location is carried out by Hough circle transform,and the center distance is calculated.The results show that the algorithm has a fast pupil location speed and can realize the automatic pupil distance measurement more accurately,which lays the foundation for the research on intelligent technologies of pupil distance measurement.