Adaptive edge detection and Histogram color segmentation for centralized vision of soccer robot

A. Aribowo, Giorgy Gunawan, H. Tjahyadi
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引用次数: 7

Abstract

In this paper an adaptive algorithm to detect arena of a soccer robot, and the position, role and orientation of robots are proposed. Adaptive edge detection using Otsu's method is used in arena detection and adaptive color segmentation using Histogram is utilized in robot detection. The proposed method is shown to be able to detect arena and robots in dynamic environment. The experiment results show that the adaptive edge detection method is able to 100% detect the arena regardless the changes in camera displacement and lighting condition. Furthermore, the histogram color segmentation successfully recognizes every significant color that exists in the arena. In the real time fashion of soccer robot, those methods give an average of 2.295% and 0.656% of error in x-axis and y-axis, respectively.
足球机器人集中视觉的自适应边缘检测和直方图颜色分割
本文提出了一种自适应的足球机器人场地检测算法,以及机器人的位置、角色和方向。竞技场检测采用Otsu方法自适应边缘检测,机器人检测采用直方图自适应颜色分割。结果表明,该方法能够在动态环境中检测竞技场和机器人。实验结果表明,无论摄像机位移和光照条件如何变化,自适应边缘检测方法都能100%检测出竞技场。此外,直方图颜色分割成功地识别了竞技场中存在的每一种重要颜色。在足球机器人的实时模式下,这些方法在x轴和y轴上的平均误差分别为2.295%和0.656%。
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