文章基本信息

标题：Multibiometric: Feature Level Fusion Using FKP Multi-Instance biometric
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作者：Harbi Almahafzah ; Mohammad Imran ; H.S. Sheshadri 等
期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2012
卷号：9
期号：4
出版社：IJCSI Press
摘要：This paper proposed the use of multi-instance feature level fusion as a means to improve the performance of Finger Knuckle Print (FKP) verification. A log-Gabor filter has been used to extract the image local orientation information, and represent the FKP features. Experiments are performed using the FKP database, which consists of 7,920 images. Results indicate that the multi-instance verification approach outperforms higher performance than using any single instance. The influence on biometric performance using feature level fusion under different fusion rules have been demonstrated in this paper.
关键词：Multi;Biometric; Multi;Instance; Feature Level Fusion; Normalization