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Attendance is a major part of any institution in the whole world. Since older times, Attendance are taken with the help of roll call manually and marked in the register and vice versa. It is a tedious task to do given the modern age we are in right now. Since, every task is automated so why not taking attendance!. Moreover, manual task involves human error which is unavoidable. In a mission to automate and modernize the attendance marking system, We created a digital attendance which marks present or absent with the help of Scanning in camera and maintaining a database in backend. This system recognize face with the help of LBPH algorithm and Haar cascading algorithms which in turn generates a facial map. The algorithm used above gives better results compared all other similar algorithms available Defining whole requirement and management is defined as a necessary step in the developing the successful software projects and systems.

The human face plays an important role in our social interaction, conveying peoples identity. Using the human face as a key to security, biometric face recognition technology has received significant attention in the past several years due to its potential for a wide variety of applications in both law enforcement and non-law enforcement. As compared with other biometrics systems using fingerprint/palmprint and iris, face recognition has distinct advantages because of its non-contact process. Face images can be captured from a distance without touching the person being identified, and the identification does not require interacting with the person.
In addition, face recognition serves the crime deterrent purpose because face images that have been recorded and archived can later help identify a person. After quitting it, attendance of person will be stored in report table in the databases with name, id, date and time and status.
This attendance system can be readily used by non-programming personal avoiding human handled chance of error. In this project apart from marking attendance by face recognition, one can register new user, update details of user and delete details. Train dataset, extract embedding’s, change password, and view the attendance report.
In this project, to recognize their face and marking their attendance, the individual had to register their details in employee management system. Then extract embedding for every new individual and then train the machine according to the sample photos taken. After that the individual is free to mark their attendance. The person can also check their attendance status, update details, delete details, check sample photos and also change the password credentials. The database is updated automatically, no need to update manually.

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