摘要
近几年对人耳这种生物特征的研究大都只能依靠手工定位和分割人耳,这大大减缓人耳识别技术的实用化进程.文中提出一种人耳自动检测方法.该方法首先利用YCbCr肤色模型和Gentle AdaBoost级联分类器检测出人耳块,然后运用改进的GVF Snake方法提取外耳轮廓.该方法通过构造耳形图,提取非常接近于人耳实际边缘的初始轮廓线,不但节省迭代时间,还提高GVF Snake提取人耳边缘的准确率,在USTB人耳库上获得约97.3%的正确检测率.实验结果表明,该方法具有较好的检测效果和鲁棒性.
In recent years the biological characteristic research of human ear can only rely on manual and then uses the improved GVF Snake method to extract the external ear contour. The method extracts the initial contour very close to the actual edge of human ear by building up the ear-shaped map. Accordingly, it not only saves iteration time, but also improves the accuracy of external ear detection in way of GVF Snake. About 97.3% of the correct detection rate is obtained on USTB ear database in our experiment. The experiment results show that the approach has better detection performance and robustness.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2010年第4期552-559,共8页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金资助项目(No.60573058)
