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A Machine Vision System for Chinese Chess-Playing Robot

机译:中国象棋机器人的机器视觉系统

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This paper introduces a machine vision system for Chinese chess-playing robots which is usually regarded as a form of recreation. The machine vision system with two color cameras takes simultaneously two images of a chessboard and round pieces on the chessboard from different angles (views). Firstly, original images are handled by a series of image processing operations such as color conversion, binarization and denoise. Secondly, a hierarchical Hough transform algorithm was taken to detect lines and circles in the binarized image. Circles with reasonable radii nearly centered on the crossings of chessboard will be considered as pieces on the chessboard and its corresponding Chinese character inside the circle would be recognized based on BP neural network and ring intersection points. The 3D coordinates of pieces can be calculated through computation and then transformed to coordinates expressed by row and column. Finally, results of image processing and pattern recognition procedures will be sent to robot control system to manipulate end-effector of a robot to move round pieces from one place to another desired. Experimental results reveal that the designed machine vision system in this paper can work well with higher reliability.
机译:本文介绍了一种中国象棋机器人的机器视觉系统,通常将其视为一种娱乐方式。具有两个彩色摄像机的机器视觉系统可以同时从不同角度(视角)拍摄棋盘和棋盘上的圆形零件的两个图像。首先,原始图像通过一系列图像处理操作进行处理,例如颜色转换,二值化和降噪。其次,采用分层霍夫变换算法检测二值化图像中的直线和圆。半径近似于棋盘交叉点的合理圆将被视为棋盘上的棋子,并根据BP神经网络和圆环相交点识别圆内其对应的汉字。零件的3D坐标可以通过计算来计算,然后转换为由行和列表示的坐标。最后,图像处理和模式识别过程的结果将发送到机器人控制系统,以操纵机器人的末端执行器,将圆形零件从一个位置移动到所需的另一位置。实验结果表明,本文设计的机器视觉系统可以很好地工作并具有较高的可靠性。

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