摘要
多生物特征融合考虑了个体的多种生理或行为特征,因而能显著地改善系统的识别性能,成为生物特征识别技术未来发展趋势之一。利用训练样本的识别率和误识率,提出了基于证据理论的多生物特征融合识别方法;对各识别专家的识别率和误识率进行分析,提出了一种基于累积频率和证据理论(Cumulative Frequency based D-S,CFDS)的多生物特征融合方法;通过几个实验证明了改进的D-S算法的有效性,提高了合成结果的可靠性。
Multi-modal biometrics techniques have shown more accurately due to the presence of multiple physiological or behavioral characteristics.Multimodal biometrics has become one of inevitable trends in the future.In this paper,D-S fusion algorithm using the recognition rate and the error rate of training set,is proposed.Then through analyzing the recognition rate and error rate,it proposes a modified multi-biometric recognition algorithm based on cumulative frequency and D-S fusion method,named CFDS.The modified D-S algorithm is applied to fusing multi-biometric.Experimental results demonstrate that the modified D-S algorithm is efficient and can improve the reliability of the combination results.
出处
《计算机工程与应用》
CSCD
2013年第18期176-179,共4页
Computer Engineering and Applications
关键词
累积频率
改进证据理论
多生物特征识别
cumulative frequency
modified D-S theory
multi-modal biometrics recognition
