简单计算机视觉系统下象棋机械臂作为基于项目的学习实例

E. Sokic, M. Ahic-Djokic
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引用次数: 21

摘要

本文介绍了基于项目的学习(PBL)在图像处理本科课程中的应用实例。讨论了一种简单、低成本的计算机视觉系统的设计,并将其应用于能下棋的机器人上。该系统是基于一个标准的CCD相机和一台个人电脑。这个项目是学习大部分课程材料的一个很好的工具,否则这些材料将被家庭作业问题和考试前的学习所掌握。提出了一种检测象棋走法的算法。它比较下棋之前、期间和之后捕获的两个或多个帧,并找到它们之间的差异,这些差异用于定义下棋的移动。进一步的图像处理需要消除错误读数,识别棋局走棋方向,最后消除图像失真。通过提出的算法,可以向学生介绍许多图像处理问题和解决方案。结果是令人鼓舞的——没有任何图像处理和高级主题知识的学生,如人工智能(神经网络等),可以在受控的光环境中获得超过95%的国际象棋走法识别成功率。
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Simple Computer Vision System for Chess Playing Robot Manipulator as a Project-based Learning Example
This paper presents an example of project-based learning (PBL) in an undergraduate course on Image processing. The design of a simple, low-cost computer vision system for implementation on a chess-playing capable robot is discussed. The system is based on a standard CCD camera and a personal computer. This project is a good tool for learning most of the course material that would otherwise be mastered by homework problems and study before an exam. An algorithm which detects chess moves is proposed. It compares two or more frames captured before, during and after a played chess move, and finds differences between them, which are used to define a played chess move. Further image processing is required to eliminate false readings, recognize direction of chess moves, end eliminate image distortion. Many Image processing problems and solutions can be introduced to students, through the proposed algorithm. The results are encouraging - students without any previous knowledge in image processing and advanced topics, such as artificial intelligence (neural networks etc.), may attain a chess move recognition success rate greater than 95%, in controlled light environments.
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