Author(s) :

Nyitamen, Dominic , Aminu, Ladodo , Ezeilo, Sunday.

Volume/Issue :

Abstract :

Biometric data capturing systems are used by employers to keep proper record of their employees’ attendance. This approach helps in checking frauds such as false attendance record which could be inevitable in manual systems. There are several available techniques involved in development of biometric attendance systems which are chosen by the developer as a matter of application and deployment of system. Some of the popular method are the fingerprint based biometric attendance system and that of voice recognition. However, attendance system would be more sophisticated if face recognition was used with combination of these techniques already mentioned. In this work a multimodal biometric attendance system has been developed. The system combines both fingerprint recognition and face recognition in taking employees’ attendance in addition to RFID card identification. The system development involved use of Machine Learning (ML) algorithm to recognize faces. The hardware was built around a single-board computer (SBC) to serve as a stand-alone system. A light-weight graphics user interface (GUI) was developed to make employees’ enrollment user-friendly. In addition to the bio capture, RFID cards were provided for each employee to use as ID card. This makes it easy to detect the presence of a worker before the system automatically prompts for capture. The system was rigorously tested, and well packaged such that provides easy access to the users

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