Automated Teachers Attendance System based on Face Recognition from live CCTV Video.

Project Title

Automated Teachers Attendance System based on Face Recognition from live CCTV Video.

Project Area of Specialization Artificial IntelligenceProject Summary

Face is the representation of one’s identity. Hence, we have proposed an automated teacher attendance system based on face recognition. Face recognition system is very useful in life applications especially in security control systems. The airport protection system uses face recognition to identify suspects and FBI (Federal Bureau of Investigation) uses face recognition for criminal investigations. In our proposed approach, firstly, video framing is performed by activating the camera through a user[1]friendly interface. The face ROI is detected and segmented from the video frame by using Viola-Jones algorithm. In the pre-processing stage, scaling of the size of images is performed if necessary in order to prevent loss of information. The median filtering is applied to remove noise followed by conversion of colour images to grayscale images. After that, contrast-limited adaptive histogram equalization (CLAHE) is implemented on images to enhance the contrast of images. In face recognition stage, enhanced local binary pattern (LBP) and principal component analysis (PCA) is applied correspondingly in order to extract the features from facial images. In our proposed approach, the enhanced local binary pattern outperform the original LBP by reducing the illumination effect and increasing the recognition rate. Next, the features extracted from the test images are compared with the features extracted from the training images. The facial images are then classified and recognized based on the best result obtained from the combination of algorithm, enhanced LBP and PCA. Finally, the attendance of the recognized teacher will be marked and saved in the excel file. The teacher who is not registered will also be able to register on the spot and notification will be given if teachers sign in more than once. The average accuracy of recognition is 100 % for good quality images, 94.12 % of low-quality images and 95.76 % for Yale face database when two images per person are trained

Project Objectives

• Reduce manual process errors by providing an automated and reliable attendance system.
• Increase privacy and security.
• Reduce time loss as time is a very valuable resource

The aim of this project is to develop a face recognition-based automated teacher attendance system. Expected achievements in order to fulfill the objectives are:

• To detect the face segment from the video frame.
• To extract the useful features from the face detected.
• To classify the features in order to recognize the face detected.
• To record the attendance of the identified teacher.

Project Implementation Method

The approach performs a face recognition-based teacher attendance system. The methodology flow begins with the capture of images by using the simple and handy interface, followed by pre-processing of the captured facial images, then feature extraction from the facial images, subjective selection, and lastly classification of the facial images to be recognized. Both LBP and PCA feature extraction methods are studied in detail and computed in this proposed approach in order to make comparisons. LBP is enhanced in this approach to reduce the illumination effect. An algorithm to combine improved LBP and PCA is also designed for subjective selection to increase accuracy.

The flow chart for the proposed system is categorized into two parts, first training of images followed by testing images (recognize the unknown input image)

1. Database Training Flow Chart Diagram

        2.  Recognition Flow Chart Diagram

Benefits of the Project

Traditional teachers’ attendance marking technique is often facing a lot of trouble. The face recognition teacher attendance system emphasizes its simplicity by eliminating classical teacher attendance marking technique such as teacher going to clerk office to mark his attendance or checking respective identification cards. There are not only disturbing the teaching process but also causes distraction for teachers during an important meeting or class. Thus, face recognition teachers’ attendance system is proposed in order to replace the manual signing of the presence of teacher which are burdensome and causes teachers get distracted in order to sign for their attendance.

Technical Details of Final Deliverable

Front End Tools

• Kivy (Python Library)

Back End Tools

• OpenCv
• Python
• Numpy(PyCharm Library)
• Openpyxl
• SQlite

Developing Tools

• PyCharm

Final Deliverable of the Project Software SystemCore Industry ITOther Industries Education Core Technology Artificial Intelligence(AI)Other Technologies OthersSustainable Development Goals Quality EducationRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	70000
Hikvision DS-2CD2785FWD-IZS 8MP IR 4K Camera Face Detection H.265+ up	Equipment	1	70000	70000