MSc Thesis Proposal Announcement of Rahul Bharadwaj Raveendran: " Effective auto grading with webcam"

 

Date: Friday December 17th, 2021 

Time:  10:00 AM – 11:30 AM  

Meeting URL:  https://us06web.zoom.us/j/88250868510?from=addon 

Passcode: If interested in attending this event, contact the Graduate Secretary at csgradinfo@uwindsor.ca with sufficient notice before the event to obtain the passcode  

Optical Mark Recognition (OMR) refers to the technique of electronically extracting data from the marked fields on the printed forms. Stemming from a hardware solution with dedicated equipment, it has gradually been replaced with emerging software technology and portable scanners. In particular, the webcam-based software solutions to OMR turn out to be more attractive due to their high affordability and flexibility. In this thesis, we propose an efficient and effective webcam-based OMR solution for auto-grading student assessment. The efficiency is achieved by maximally dropping the requirements on the operations of the end-users. The effectiveness is understood together with the handling of the technical difficulties originated from the factors like the distance between the grading sheet and the webcam, the rotation and orientation of the grading sheet, the brightness of the environment, etc. Various present OpenCV image processing techniques are combined to accurately identify the region of interest and the reference points on the grading sheet. This is followed by a specific algorithm to detect the orientation of the grading sheet. The proposed solution tries to maximize the acceptable operations and aims at providing 100% accurate grading among those accepted ones. The experiments will be performed to compare the proposed method with the existing ones in terms of operational time and accuracy. 

 

Keywords: Image processing, Optical Mark Recognition, OpenCV 

 

 

Internal Reader: Dr. Ikjot Saini           

External Reader: Dr. Balakumar Balasingam  

Advisor: Dr. Jessica Chen