Intelligent segmentation of subjective question area by removing template in intelligent marking

Haihui Xin; Shanshan Zhang

doi:10.1117/12.2655995

12 January 2023 Intelligent segmentation of subjective question area by removing template in intelligent marking

Haihui Xin, Shanshan Zhang

Proceedings Volume 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022); 125090J (2023) https://doi.org/10.1117/12.2655995
Event: Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 2022, Guangzhou, China

Abstract

With the rapid development of computer technology and communication technology, computers have been applied to all areas of people's lives. In the field of education, it is a necessary function for the intellectualization of the education system to realize the automatic marking of examination papers by computer. In intelligent marking, the traditional method is used to segment the subjective question area of the test paper, which can not effectively segment different types of answer sheets and has the defects of low segmentation accuracy. The edge detection method is used to correct the subjective question area of the answer sheet, and the boundary box of the subjective question part is accurately screened by positioning the top, left, and bottom positioning lines of the answer sheet to complete the segmentation of the subjective question area in marking. The experimental results show that the correct rate of the new method is more than 95%, which is much higher than that of the traditional method. The new method can be widely used in intelligent marking work, and can effectively improve the efficiency of intelligent marking.

Citation Download Citation

Haihui Xin and Shanshan Zhang "Intelligent segmentation of subjective question area by removing template in intelligent marking", Proc. SPIE 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 125090J (12 January 2023); https://doi.org/10.1117/12.2655995

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