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Recognition and Separation of Objects on a Lego Mindstorms NXT Conveyor Belt Using Log-Polar Transform and Artificial Neural Networks

机译:使用逻辑极化变换和人工神经网络识别和分离乐高态度NXT传送带NXT输送带

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This paper treats the implementation of a computer vision system to do the recognition and separation of objects that are put into a conveyor belt, built with a Lego Mind storms NXTtext superscript{text registered} kit. The image acquisition is made through a web cam upon the specific capture area. After the image have been sent to a computer, a preprocessing made by Matlabtext superscript{text registered} extracts only the main characteristics of the object, e.g., removing the background. Due to rotation and translation of the parts, a Log-Polar Transform (LPT) is used to avoid these effects. The LPT response is used as input to an Artificial Neural Network, able to classify the objects and send the information to the conveyor belt, which separates equal objects in the same place.
机译:本文对计算机视觉系统的实施进行了处理,以便进行将物体放入传送带的物体的识别和分离,并用乐高思维风暴建造NXTText上标{Text注册}套件。图像采集通过在特定捕获区域上通过Web Cam进行。在将图像发送到计算机后,MatlabText上标的预处理{Text注册}仅提取对象的主要特征,例如,删除背景。由于零件的旋转和翻译,用于避免这些效果的逻辑极性变换(LPT)。 LPT响应用作人工神经网络的输入,能够对物体进行分类并将信息发送到传送带,该传送带将相同的物体分开在同一位置。

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