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Research on Machine Instrument Panel Digit Character Segmentation
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Author(s): Xiaoyuan Wang (Basic Teaching and Training Center, Hefei City, China), Hongfei Wang (Sinosoft Company Limited, China), Jianping Wang (College of Electrical Automation, Hefei University of Technology, China)and Jiajia Wang (Student Innovation and Entrepreneurship Education Center, Hefei University, China)
Copyright: 2024
Volume: 17
Issue: 1
Pages: 24
Source title:
International Journal of Information Technologies and Systems Approach (IJITSA)
Editor(s)-in-Chief: Sangbing (Jason) Tsai (International Engineering and Technology Institute (IETI), Hong Kong)and Wei Liu (Qingdao University, China)
DOI: 10.4018/IJITSA.335941
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Abstract
In this study, the authors perform slant correction on fixed-format dial images using the Hough transform, followed by their “scaling” using binary wavelets to achieve coarse segmentation for characters or numbers. Simultaneously, they propose a binary threshold iteration method that accurately determines the position of each character or number even in the presence of adhesion or fragmentation, enabling precise segmentation. They employ their proposed approach to segment digits and characters displayed on 98 fixed-format dials. Experimental results demonstrate a recognition rate of 98.5% for both letters and numbers, highlighting significant practical value and real-world implications.
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