JJEM: Special Edition 2 (December 2024)
JJEM: Special Edition 2 (December 2024)
2024-12-08
Optical Mark Recognition Automated Grading system using OpenCv-based Image Processing.
Shivani Adiga, Manjunatha H T
The OpenCV-based image processing is used by the Optical Mark Recognition (OMR) automated grading system to analyze blue-gray scale images with robust edge detection. To reduce noise, the system preprocesses images by converting them to grayscale and using Gaussian blur. Smart edge detection recognizes sharp edges and differentiating marks on the OMR sheet. To improve the accuracy of the analysis, rectangular contours possibly around OMR sections are extracted and corrected using perspective transformation for a flat sheet view. Answer bubbles are divided into segments and then thresholded to produce binary images. This OpenCV-based system ensures accurate and dependable grading by efficiently handling different OMR formats and Image quality variations. It is platform independent for simple integration into a variety of learning and testing environments and it minimizes processing time and human error, making it perfect for large-scale evaluations.
Optical Mark Recognition, Image Preprocessing, edge detection, thresholding techniques