基于人脸和人耳的多模态生物特征识别

单一模式生物特征识别系统由于存在一些固有的局限性,有时难以满足实际应用的需求,本文提出了基于正面人脸和人耳信息融合的多模态生物特征识别方法.针对USTB人耳图像库和ORL人脸图像库,利用核Fisher鉴别分析方法分别进行了人耳识别、人脸识别和人脸人耳融合识别,融合策略包括图像层融合和特征层融合两种.识别结果表明基于人脸人耳信息融合的多模态识别的识别率优于单体的人耳或人脸识别.这说明融合多种生物特征的多模态识别可以提高身份认证的准确率,也为实现非打扰式识别提供了一种新的途径.

Multimodal recognition using face and ear

Unimodal biometric systems have to contend with a variety of problems and sometimes cannot satisfy application requirements.In this paper,a novel method of multimodal recognition using frontal face and ear was proposed.Kernel Fisher Discriminant Analysis was used for ear recognition,face recognition and the multimodal recognition.The multimodal recognition was studied on the image level fusion and feature level fusion.The experimental results from using USTB ear database and ORL face database show that the multimodal recognition outperforms the unimodal biometric recognition.This work shows that multibiometric system can increase the accuracy of overall system recognition,and provides an effective approach of non-intrusive biometric recognition.