计算机科学与应用

Vol.2 No.5 (December 2012)

基于几何特征的疲劳检测算法研究与实现
Implementation of Fatigue Detection Algorithm Based on Geometric Features

 

作者:

王景丹 , 江春华 , 郝宗波 :电子科技大学计算机科学与工程学院

 

关键词:

图像预处理分类器几何特征疲劳状态Image Pre-Processing Classifier Geometric Features Fatigue State

 

摘要:

采用基于人脸分类器的Adaboost算法可以准确检测并定位人脸,然后通过尝试帧差法及几何特征法来定位人眼,提取人眼图像,进行灰度化、高斯平滑、自适应阈值等预处理,最终获取人眼二值化图像,进一步精确到眼睛部位,分析眼睛的状态特征,判定驾驶员是否处于疲劳状态。实验结果表明几何特征定位人眼的方法有抗干扰的效果,眼睛特征表现明显,鲁棒性好,同时也能够保证实时性。

The Adaboost algorithm based on the face of the classifier can accurately detect and positioning face, then through trying three methods to locate the human eye, such as Frame Difference and geometric feature method, extracting human eye image to obtain the binary image of eye by gray processing, gauss smooth, adaptive threshold. Finally, the algorithm will further accurately judge the driver is in a state of fatigue through the analysis of eyes’ feature. The experimental results show that the method of Geometric Feature has anti-jamming effect in positioning the human eye, and the eyes feature significantly can ensure Robustness and real-time.

文章引用:

王景丹 , 江春华 , 郝宗波 (2012) 基于几何特征的疲劳检测算法研究与实现。 计算机科学与应用, 2, 246-250. doi: 10.12677/CSA.2012.25043

 

分享
Top