| dc.description.abstract | In this digital era, face recognition system plays a vital role in almost
every sector. Face recognition is one of the mostly used biometrics. It can used
for security, authentication, identification, and has got many more advantages.
Despite of having low accuracy when compared to iris recognition and
fingerprint recognition, it is being widely used due to its contactless and non invasive process. Furthermore, face recognition system can also be used for
attendance marking in schools, colleges, offices, etc. This system aims to build
a class attendance system which uses the concept of face recognition as
existing manual attendance system is time consuming and cumbersome to
maintain. And there may be chances of proxy attendance. Thus, the need for
this system increases. This system consists of four phasesdatabase creation,
face detection, face recognition, attendance updation. Database is created by
the images of the students in class. Face detection and recognition is
performed using HaarCascade classifier and Local Binary Pattern Histogram
algorithm respectively. Faces are detected and recognized from live streaming
video of the classroom. Attendance will be mailed to the respective faculty at
the end of the session. Technology used : -open CV (Open source Computer
Vision) -Python – tkinter GUI interface . The cropped images are then stored as
a database with respective labels. The features are extracted using LBPH
algorithm. | en_US |
