Abstract
In order to solve the problem that the efficiency of smart classroom is not high enough, a multi valued color image segmentation algorithm based on CAD is proposed to optimize the smart classroom. This paper explores the notion of smart education as well as a conceptual framework to enable children to receive excellent education and to spark their interest through creative learning. Firstly, CAD software is used to improve software design efficiency and optimize product technology; Secondly, the core technology of the smart classroom is improved by using the national value color image segmentation algorithm, and compared with the smart classroom without the multi value color image segmentation algorithm; Finally, the utilization efficiency of the improved smart classroom is counted. It is proved that the smart classroom based on CAD multi valued color image segmentation algorithm can give greater play to the role of smart classroom, reduce the teaching pressure of teachers by 20% and improve the learning efficiency of students by 20%. The intelligent classroom has a higher degree of informatization and more powerful functions, which is of great help to promote classroom communication and improve communication efficiency. The smart classroom is easier to run and adapt thanks to the optimization of the CAD multi threshold color picture segmentation algorithm, which considerably improves the system's work efficiency and capability. However, the smart classroom also has its own shortcomings, which are mainly reflected in the high investment cost, the complex design of the system and the high maintenance cost in the later stage. With the optimization of CAD multi valued color image segmentation algorithm, the smart classroom is easier to operate and adjust, which greatly enhances the work efficiency and ability of the system.
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Wang, N., Li, J., Balaji, P., Vaiyapuri, T., & Verma, A. (2023). Optimization of Intelligent Classroom based on CAD Multi-Valued Color Image Segmentation Algorithm. Computer-Aided Design and Applications, 20(S3), 16–28. https://doi.org/10.14733/cadaps.2023.S3.16-28
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