Automated attendance management system using face recognition

Abstract

Face Detection and Recognition is an important area in the
field of substantiation. Maintenance of records of students
along with monitoring of class attendance is an area of
administration that requires significant amount of time and
efforts for management. Automated Attendance Management
System performs the daily activities of attendance analysis,
for which face recognition is an important aspect. The
prevalent techniques and methodologies for detecting and
recognizing face like PCA-LDA, etc fail to overcome issues
such as scaling, pose, illumination, variations, rotation, and
occlusions. The proposed system provides features such as
detection of faces, extraction of the features, detection of
extracted features, analysis of students' attendance and
monthly attendance report generation. The proposed system
integrates techniques such as image contrasts, integral images,
Ada-Boost, Haar-like features and cascading classifier for
feature detection. Faces are recognized using advanced LBP
using the database that contains images of students and is used
to recognize student using the captured image. Better
accuracy is attained in results and the system takes into
account the changes that occurs in the face over the period of
time.