一种基于AdaBoost算法的增强生物特征评分融合方案

Wei-Yang Lin, Chuan-Jheng Yang
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引用次数: 3

摘要

生物识别系统中的信息融合,无论是多模态融合还是模态内融合,通常都能提高识别性能。提出了一种新的分数级融合方案——增强分数融合。提出的框架是一个两阶段的设计,第一阶段采用现有的融合算法。在第二阶段,利用AdaBoost算法获得的权重来提高先前融合结果的性能。实验结果表明,采用该方法可以提高几种分数级融合方法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An enhanced biometric score fusion scheme based on the AdaBoost algorithm
Information fusion in biometric systems, either multimodal or intramodal fusion, usually provides an improvement in recognition performance. This paper presents a novel score-level fusion scheme called boosted score fusion. The proposed framework is a two-stage design where an existing fusion algorithm is adopted at the first stage. At the second stage, the weights obtained by the AdaBoost algorithm are utilized to boost the performance of the previously fused results. The experimental results demonstrate that the performance of several score-level fusion methods can be improved by using the presented method.
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