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JCST

Journal of Current Science and Technology

ISSN 2630-0583 (Print)

ISSN 2630-0656 (Online)

Effecting of environmental conditions to accuracy rates of face recognition based on IoT solution

  • Meennapa Rukhiran, Department of Social Technology Ragamangala University of Technology Tawan-OK, Chanthaburi, Thailand
  • Paniti Netinant, College of Information and Communication Technology, Rangsit University, Bangkok, Thailand, Corresponding author; E-mail: paniti.n@rsu.ac.th
  • Tzilla Elrad, Concurrent Programming Research Group, Illinois Institute of Technology, IL, Chicago, 60616, USA

Abstract

There are an increasing number of Internet of Thing (IoT) solutions that are treated and supported us in communication, data storage, maintenance, monitoring, privacy, and security.  Advances in face recognition have provided efficiency and security that can be developed through IoT devices for the cheaper prices than the past.  Face recognition enables the development on the camera through Raspberry PI 3 importing a machine learning algorithm in the easy way.  However, the use of a camera and a face recognition system on IoT can be particularly found missing detection and recognition problems.  The challenges on developing the face recognition system has been encouraging, the accuracy progress of face recognition turn out to be many conditions.  In our view, the developing recognition procedure is able to discovery the relationships of the factors related to the correctness of a face recognition system in the different conditions of image resolutions, distances, and illuminations.  This article discusses the appropriate conditions for the better condition tasks of image resolutions and distances.  Finally, we propose the operational semantic, which can calculate on the different environment conditions and shows results that demonstrate the better accuracy rates of the sufficient preparation for face recognition systems.

Keywords: accuracy rate, face detection, face recognition, image resolution, IoT, lighting

PDF (1.12 MB)

DOI: 10.14456/jcst.2020.2

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Approved By TCI (2020 - 2024)

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