文章基本信息

标题：HYBRID HAND-DIRECTIONAL GESTURES FOR BAIOMETRIC BASED ON AREA FEATURE EXTRACTION AND EXPERT SYSTEM
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作者：FAHAD LAYTH MALALLAH ; BARAA T. SHAREF ; ASO MOHAMMAD DARWESH 等
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：2017
卷号：95
期号：23
页码：6546
出版社：Journal of Theoretical and Applied
摘要：Nowadays, biometric authentication researches are becoming one of the major focuses among researchers due to various fraud attempts are taking place. Although, several authentication operations are available, these are not free of defects that affect negatively on the authentication operation. Therefore, a novel technique is proposed using index-finger of a hand in order to point out random directions such as up, down, left, or right. Accordingly, a new feature extraction based on area of the index-finger is proposed. It is hybrid between static and dynamic hand directional gesture recognition having advantage that is not forgettable as password due to biologically that this gesture is stored in the brain as visual memory type. This method starts by recording a video around 2-10 seconds as time duration, and then frames are processed one by one to output 4-set-direction, which are deemed as passwords for an individual. Later on, extracted gesture direction vector is matched against the stored one, to output either accept or reject status. Experiments were conducted on 60-video frames were prepared for training and testing recorded from 10 individuals. Result findings demonstrate high successful recognition rate as the performance accuracy is 98.4% of this proposed method.
关键词：Biometrics; Hand Gesture; Pattern Recognition; Feature Extraction; Expert System; Computer Vision; Data Science.