<![CDATA[The high costs associated with specialized scanning devices for computer-based answer sheets (LJK) present significant barriers for educational institutions, especially those in underfunded or rural areas. This research introduces an application utilizing the Canny edge detection algorithm to process and evaluate LJK responses efficiently and accurately. The proposed system employs advanced image processing techniques to detect marked answers and automate scoring based on a pre-configured answer key, significantly reducing manual errors. Python programming was used to develop the application, leveraging its robust libraries and flexibility. The system demonstrated reliable edge detection and efficient response evaluation in various testing scenarios. This approach provides a scalable and cost-effective alternative to manual grading systems or expensive scanning devices, potentially transforming how assessments are handled in educational institutions.]]>
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