Attendance Capturing and Consolidation Mechanism Using Image Processing and Machine Learning Technique

Reorganization of hand written text needs natural intelligence. The proposed method recognizes the handwritten characters and classifies them from other characters for the attendance calculation system. The manual procedure for totaling students' attendance from the attendance register is difficult and time-consuming. The existing manual process for counting students' attendance contains a laborious effort for the number of students present or absent in a class. We propose an automated, digitized method for calculating the total number of presents or absent for a student in a class.

The proposed system uses features extraction from a character, using feature extraction techniques. Support vector machine is one of the machine learning techniques used to classify a handwritten character. Support vector machine is trained using a large number of the training data set that needs to be fed into the database for accurate output. SVM is suitable and provides all the most desired levels of output. One Graphical User Interface(GUI) guides a user for stepwise visualization of the operations.

Our objective is to minimize manual efforts and automate attendance counting more structured way.