Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{202642,
        author = {Ritesh Adling and Nikhil hajare and Snehal Sakhare and Satyam yadav},
        title = {Smart Attendance System Using Face Recognization},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {12188-12191},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=202642},
        abstract = {In many schools and colleges, taking attendance manually is a time-consuming task and often leads to errors such as proxy attendance. To solve this problem, this project presents a Smart Attendance Management System that uses face recognition technology to automate the attendance process in an efficient and reliable way.The system captures live video through a webcam and processes it using OpenCV to detect faces in real time. For recognizing the faces, the LBPH (Local Binary Pattern Histogram) algorithm is used, which compares the detected face with stored images of students in the dataset. Once a match is found, the system automatically marks attendance along with the date and time. In addition to marking attendance, the system also analyzes the attendance records and generates useful reports such as defaulter lists (students below 75% attendance) and eligible lists (students with 75% or above attendance). This helps teachers easily monitor student participation without manual calculations. The proposed system is simple, cost-effective, and reduces human effort while improving accuracy. It can be used in classrooms to ensure fair attendance management and prevent misuse such as proxy attendance. Overall, this project provides a smart and practical solution for modern educational environments.},
        keywords = {Face Recognition, Smart Attendance System, OpenCV, LBPH (Local Binary Pattern Histogram)},
        month = {May},
        }