文章基本信息

标题：INDIVIDUALITY REPRESENTATION USING MULTIMODAL BIOMETRICS WITH ASPECT UNIETED MOMENT INVARIANT FOR IDENTICAL TWINS
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作者：BAYAN OMAR MOHAMMED ; SITI ZAITON MOHD HASHIM
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2020
卷号：98
期号：12
页码：2148-2157
出版社：Journal of Theoretical and Applied
摘要：In essence, a biometric system comprises a pattern recognition system that obtains a personâ€™s biometric data from which a feature is set and then extracted. Upon setting the feature, it is compared to the template set stored in the database. Biometric identification systems need to not only have the capacity to distinguish between individuals but to also be capable of distinguishing individuals with nearly identical biometric signatures, such as identical twins. Multimodal biometric systems are therefore currently more popular because of their higher accuracy level in comparison to unimodal biometric systems in the context of identical twins. Comparatively, these systems require the extraction and selection of meaningful features. This paper introduces a new method for a multimodal biometric system using the Aspect United Moment Invariant for global feature extractions to detect identical twins. An experimental data set comprised of 1600 images from 100 pairs of identical twins collected from the Kurdistan region in Iraq is utilized.
关键词：Multi-Biometric;Identical Twin;Identification;Global Features;Aspect United Moment Invariant (AUMI).