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, 2022)
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.