Automated Examination Paper Correction via OCR Position Matching
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Solution Overview
Problem
The inefficiency and error-prone nature of traditional manual methods for correcting examination papers, which require significant time and effort from teachers.
Innovation Solution
An automated examination paper correction method using pre-trained identification models to mark and compare answers in standard and corrected examination papers, determining position information and character content to facilitate accurate and rapid correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual handwriting correction is used, then teachers can correct examination papers, but the efficiency is low and errors are prone to occur
Solution Approach 1:
The patent replaces the manual mechanical correction process with an automated optical character recognition (OCR) system. The system scans examination papers, extracts answer content through OCR technology, compares answers automatically, and generates correction results, eliminating the need for teachers to manually grade each paper by hand.
Solution Approach 2:
The correction system performs self-service by automatically processing the entire correction workflow without human intervention. The system independently completes image acquisition, character recognition, answer comparison, and result generation, making the correction process autonomous and efficient.
2Productivity
If manual correction is used, then teachers can provide feedback, but the process is time-consuming and labor-intensive
Solution Approach 1:
The correction system is divided into distinct functional modules: image acquisition module, character recognition module, answer comparison module, and result generation module. Each module performs a specific function independently, making the overall complex process manageable and scalable through modular architecture.
Solution Approach 2:
The patent introduces an intermediary character recognition model that bridges the gap between image processing and answer comparison. This intermediary layer extracts and standardizes answer content from scanned images, enabling accurate automated comparison without direct complex interaction between all system components.
3Extent of automation
If automated correction is implemented, then correction efficiency improves, but the system complexity increases
Solution Approach 1:
The character recognition model serves multiple functions: it recognizes characters in standard answers, extracts answer content from student papers, and provides data for comparison. This multi-functionality reduces the need for separate specialized components, simplifying the overall system architecture while maintaining high automation.
Data Source
AI summary
An examination paper correction method and apparatus, an electronic device, and a storage medium are provided. The method includes: obtaining a first image of a standard examination paper; identifying an area and characters of each standard answer in the first image, and using a marking box to mark an answering area where each standard answer is located; determining position information of each marking box; obtaining a second image of an examination paper to be corrected; determining, according to the position information of each marking box of the first image, an answering area in the second image matching a position of the marking box, and using a marking box to mark the determined answering area; identifying characters of an answer to be corrected in each marking box of the second image; and comparing the characters of the standard answer with the characters of the answer to be corrected.