人脸图像中人眼的检测与定位

Detecting and locating human eyes in face images

利用人脸几何特征和图像分割原理,提出了一种在有背景的灰度和彩色人脸图像中自动检测与定位人眼的新算法。首先,基于人脸器官几何分布先验知识建立人眼位置判定准则;其次对人眼的分割阈值范围进行粗估计;然后采用分割阈值递增法,并结合人眼位置判定准则判定分割图像中双眼黑块是否出现;最后利用二维相关系数作为对称相似性测度,检验检测到的双眼的真实性。为了避免图像背景对人眼检测的干扰,还运用了肤色分割原理来缩小检测人眼的搜索区域,从而进一步提高人眼定位的准确性。实验验证表明,所提出的人眼检测与定位方法在速度和准确性方面具有良好的性能。

A novel algorithm for automatic detection and localization of human eyes in grayscale or color still face images with backgrounds is presented based on geometrical facial features and image segmentation. First of all, a determination criterion of eye location is established by the prior knowledge of geometrical facial features. Secondly, a range of threshold values that would separate eye blocks from others in a segmented face image （i.e., a binary image） is estimated. Thirdly, with the progressive increase of the＂ threshold by an appropriate step in that range, once two eye blocks appear from the segmented image, they will be detected by the determination criterion of eye location. Finally, the 2-D correlation coefficient is used as a symmetry similarity measure to check the factuality of the two detected eyes. To avoid the background interference, skin color segmentation can be applied in order to enhance the accuracy of eye detection. The experimental results demonstrate the high efficiency of the proposed algorithm in runtime and correct localization rate.