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Intelligent pattern recognition in 3D vision for robot control

机译:机器人控制3D视觉中的智能模式识别

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Proposes a recognition method by which 3D information of overlapped objects can be constructed, taking into account the fuzzy quantities of linearity and roundedness of image data. The recognition approach was based on grey-level image processing as well as color and binary image processing. Grey-level image data were used for classifying the image patterns into the specific candidate group. Then the other data are obtained by changing the attitude of the objects slightly, so that the 3D image data can be reconstructed for pattern recognition and understanding. An expert system for the pattern recognition and the understanding of objects is constructed based on a production system. The system gives commands to rotate the objects in a certain direction to increase the image information about the objects until they can be identified.
机译:提出可以构建重叠对象的3D信息的识别方法,考虑到图像数据的线性和圆度的模糊量和圆形。识别方法基于灰度图像处理以及颜色和二进制图像处理。灰度级图像数据用于将图像模式分类为特定候选组。然后通过稍微改变对象的姿态来获得其他数据,从而可以重建3D图像数据以用于模式识别和理解。基于生产系统构建了模式识别的专家系统和对象的理解。系统给出命令以在某个方向上旋转对象以增加关于对象的图像信息,直到可以识别它们。

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