改进单尺度Retinex的复杂光照人脸识别算法  

FACE RECOGNITION ALGORITHM IN COMPLEX ILLUMINATION CONDITIONS WITH IMPROVED SINGLE-SCALE RETINEX

作　　者：朱珍[1] 万志平[2] 蒋鹏[3] 

机构地区：[1]广东工程职业技术学院,广东广州510520 [2]浙江工业职业技术学院,浙江绍兴312000 [3]杭州电子科技大学,浙江杭州310018

出　　处：《计算机应用与软件》2014年第3期246-249,262,共5页Computer Applications and Software

基　　金：国家自然科学基金项目(61273072)

摘　　要：在光照复杂条件下人脸识别性能明显下降。针对单尺度Retinex算法易产生"光晕"现象,提出一种改进单尺度Retinex算法的复杂光照人脸识别方法(ISSR)。首先利用拉普拉斯梯度算子增强光照人脸图像的边缘信息,然后在单尺度Retinex算法的基础引入符合人眼视觉特性的中心自适应调节拟合函数,以增强图像各个颜色分量,提高人脸图像对比度,最后采用Yale B和CMU-PIE人脸库进行仿真测试。结果表明,ISSR算法增强了人脸图像的对比度,改善了人脸图像的视觉效果,有助于提高人脸图像识别率和识别速度,能满足复杂光照条件下的人脸识别要求。Under complex illumination conditions, face recognition performance declines dramatically, the single-scale Retinex algorithm is easy to produce ＂halo＂ phenomenon. Aiming at this, we propose a complex illumination face recognition method which is based on im- proved single-scale Retinex algorithm. First, the Laplace gradient operator is used to enhance the edge information of lightened face images, and then based on single-scale Retinex algorithm the centre adaptive adjustment fitting function in accord with human visual system is intro- duced to enhance each colour component of the image and to improve the contrast of face image. Finally Yale B and CMU-PIE face database are used for simulation test. Results show that the proposed method enhances the contrast of face image, improves face image visual effect, and is conducive to improving face recognition rate and recognition speed, it can meet the requirements of face recognition under complex illu- mination conditions.

关 键 词：人脸图像 图像增强 色彩恒常理论 支持向量机 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]