Attendance Management System using Face Recognition

Authors: Anuradha Yadav, Sunil Kumar, Vikash Gupta, Sumit Kumar

DOI: https://doi.org/10.5281/zenodo.7577140

Short DOI: https://doi.org/grpwzf

Country: India

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Abstract: Managing attendance can be a tedious job when implemented by traditional methods like calling out roll calls or taking a student's signature. To solve this issue, a smart and authenticated attendance system needs to be implemented. Generally, biometrics such as face recognition, fingerprint, DNA, retina, iris recognition, hand geometry etc. are used to execute smart attendance systems. Face is a uniqueidentification of humans due to their distinct facial features.Face recognition systems are useful in many real-life applications. In the proposed system, initially all the studentswill be enrolled by storing their facial images with a unique ID. At the time of attendance, real time images will be captured and the faces in those images will be matched with the faces in the pre-trained dataset. The Haarcascade algorithm is used for face detection. Local Binary Patterns Histogram (LBPH) algorithmis used for face recognition and training the stored dataset that generates the histogram for stored images and the real time image. To recognize the face, the difference between histograms of real time image & dataset images is calculated. Lower difference gives the best match resulting in displaying the name & rolls number of that student. Attendance of the student is automatically updated in the excel sheet.

Keywords: Face Detection, Face Recognition, Haar Cascade Classifier, Local Binary Pattern Histogram, LBPH

Paper Id: 230006

Published On: 2023-01-28

Published In: Volume 11, Issue 1, January-February 2023

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