Abstract
This paper presents the development of a test paper checker that will recognize a handwritten text using Intelligent Character Recognition (ICR) for Alphanumeric Characters. An examination can be conducted in two ways—digital and manual—and each way has a different approach in checking. In this study, the main objective is to recognize alphanumeric handwritten characters accurately using intelligent character recognition. OpenCV is used in the Python programming language and Support Vector Machine as a tool in machine learning for ICR. Answer sheet was designed with 120 items for MCQ and problem-solving questions. Item analysis and printing of results are included in the device. Experiments were conducted by giving an actual examination from the 131 participants in Technological University of the Philippines for testing the accuracy of the device. The results obtained from comparing manual and machine checking had an accuracy of 93.0769%. Thus, the proposed method is applicable for the development of handwritten character recognition.
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Velasco, J.S. et al. (2020). Alphanumeric Test Paper Checker Through Intelligent Character Recognition Using OpenCV and Support Vector Machine. In: Beltran Jr., A., Lontoc, Z., Conde, B., Serfa Juan, R., Dizon, J. (eds) World Congress on Engineering and Technology; Innovation and its Sustainability 2018. WCETIS 2018. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-20904-9_9
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