In both academics and business, tracking attendance is a crucial administrative procedure. Current techniques, including manual roll calls, RFID cards, barcode IDs, and fingerprint scanners, are inefficient, prone to manipulation, and have environmental restrictions and hygienic issues. Face-recognition systems have gained popularity because they are frictionless and easy to use, but they still have drawbacks including illumination variations, position changes, complex backgrounds, occlusions, and individual facial similarities. This study suggests a hybrid Face and Uniform-Based Attendance System that combines uniform pattern and color-based identification with facial recognition. By significantly lowering impersonation and proxy attendance, the dual-authentication approach increases accuracy and dependability. The system performs better in a variety of real-world scenarios by using LBPH for facial recognition and HSV-based segmentation for consistent identification. When compared to face-only systems, experiments show a 35% decrease in false positives. A thorough literature analysis, theoretical background, methodology, system design, algorithmic breakdown, experiments, evaluation measures, benefits, drawbacks, and potential improvements are all included in this expanded study
Singh et al. (Fri,) studied this question.