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Neural network based image recognition system using geometrical moment

机译:基于神经网络的图像识别系统使用几何时刻

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Geometrical moments (GM) have been used in the classification of four closed planar shapes (Gupta and Srinath, 1987). Also a neural network approach for the classification of four closed planar shapes has been used in Khotanzad and Lu (1990). In this paper, a backpropagation neural network is used in the recognition of six different kinds of hand tools using geometrical moments. Experimental results indicate that the neural network approach gives a better recognition accuracy when compared with the two conventional statistical classifiers-namely the single nearest neighbour and minimum-mean-distance. Recognition accuracy using a neural network is over 98%.
机译:几何时刻(GM)已用于四个封闭的平面形状(Gupta和Srinath,1987)的分类。此外,Khotanzad和Lu(1990)也使用了用于四个闭式平面形状的神经网络方法。在本文中,使用几何时刻识别六种不同手动工具的反向桥断神经网络。实验结果表明,与两个传统的统计分类器相比,神经网络方法给出了更好的识别准确性 - 即单个最接近邻居和最小平均距离。使用神经网络的识别准确度超过98%。

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