Exam Marks Summation App Using Tesseract OCR in Python

Authors

  • Kalaimathi Saravanan Department of Electronic Engineering, Faculty of Electrical and Electronic Universiti Tun Hussein Onn Malaysia
  • Chang Choon Chew Department of Electronic Engineering, Faculty of Electrical and Electronic Universiti Tun Hussein Onn Malaysia
  • Kim Gaik Tay Department of Electronic Engineering, Faculty of Electrical and Electronic Universiti Tun Hussein Onn Malaysia
  • Sie Long Kek Department of Mathematics and Statistics, Faculty of Applied Science and Technology, Universiti Tun Hussein Onn Malaysia
  • Audrey Huong Department of Mathematics and Statistics, Faculty of Applied Science and Technology, Universiti Tun Hussein Onn Malaysia

Keywords:

summation, Tesseract, OCR, Python, App

Abstract

There are no tools to auto grade subjective questions and no auto summations app to date. As a result, examiners need to mark subjective answer scripts manually and they might overlook some marks while summing up subjective answer scripts scores obtained by students. Therefore, this study aims to develop an exam mark summation app to ease miscalculation problems. Tesseract OCR was implemented in this Marks Summation App as a platform to scan the multi-page handwritten marks using pen tip above a 0.5mm size in red, blue, and black to recognise the marks wrote by the examiners. The captured marks images will be uploaded to server for image processing by promptly executing the python script in the server. The extraction of numbers from the processed image will sum up the scores to determine each candidate's final score. It is recommendable to scan the original materials to produce more accurate accuracy. Out of 118 numbers from 21 testing samples, 88 numbers are correctly recognised, whereas 30 are not recognised correctly. Thus, the accuracy of the developed exam mark summation app is 74.58%. The app's performance is more superior than car plate recognition result in the field. In the future, we hope to increase the app’s recognition accuracy by exploring deep learning in recognizing handwritten numbers.

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Published

22-06-2022

How to Cite

Saravanan, K. ., Chew, C. C., Tay, K. G., Kek, S. L., & Huong, A. (2022). Exam Marks Summation App Using Tesseract OCR in Python. International Journal of Integrated Engineering, 14(3), 102–110. Retrieved from https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/10516