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A comparison of classification algorithms for chess pieces detection

机译:棋章检测分类算法的比较

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This work presents an evaluation of different classification algorithms to be implemented in a computer vision system to detect chess pieces. The implementation consists of a mechatronic system that allows a person to play chess against a robot manipulator and on a standard board. The system is based on an industrial type robot, a webcam-based artificial vision subsystem and open software for the game engine. The vision subsystem features a webcam that captures photos from the board. The aim is to detect, by means of classification techniques, whether a square is occupied by a piece, and in such a case whether the piece is black or white. Using matrix models, it is possible to determine the last movement executed by the human opponent. Robotics applied to interactive games is an excellent problem to explore human-robot collaboration as it presents a structure whose complexity can be gradually increased.
机译:该工作介绍了在计算机视觉系统中实现不同分类算法的评估,以检测棋子。该实施包括机电系统,允许一个人在机器人操纵器和标准板上播放国际象棋。该系统基于工业型机器人,基于网络摄像头的人工视觉子系统和游戏引擎的开放软件。 Vision子系统具有从电路板捕获照片的网络摄像头。目的是通过分类技术来检测范围是否被一块占据,并且在这种情况下是黑色或白色。使用矩阵模型,可以确定人类对手执行的最后一个运动。应用于交互式游戏的机器人是探索人员机器人协作的一个很好的问题,因为它具有逐渐增加的复杂性的结构。

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