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Subasi Tziritas Ezema
Meiji University, Tokyo, Japan
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Optimizing face sensor-based attendance system using wavelet method for enhanced security and efficiency Priya Shimizu; Hagihara Kobatake; Subasi Tziritas Ezema; Maiti Eneh Bhanot; Das Junior
Vertex Vol. 11 No. 2 (2022): June: Engineering
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/629k6b98

Abstract

In today’s digital era, efficient and accurate attendance management is essential in various sector. This research presents an innovative approach in the development of facial sensor-based attendance systems using the wavelet method. This approach aims to address the challenges of recognizing faces under varying lighting conditions, rotations, and facial details. Image pre-processing is used to improve the quality of the face image, followed by a discrete wavelet transform to decompose the image into wavelet coefficients at various scales. This model is strengthened by strong security techniques, considering the importance of individual data privacy. This research offers a modern alternative in attendance management by utilizing facial recognition technology and the wavelet method. Although the mathematically formulated model provides a clear framework, practical implementation requires advanced techniques in image processing and artificial intelligence.
Co-Authors Das Junior Hagihara Kobatake Maiti Eneh Bhanot Priya Shimizu