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Invariant Ridgelet-Fourier Descriptor for Pattern Recognition

机译:不变的Ridgelet-Fourier描述符,用于模式识别

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In this paper, we present a novel descriptor for feature extraction by using a combination of ridgelets and Fourier transform. We have successfully implemented ridgelets on the circular disk containing the pattern and applied Fourier transform on the resulting ridgelet coefficients to extract rotation-invariant features for pattern recognition. The descriptor is very robust to Gaussian noise even when the noise level is high. Experimental results show that the new descriptor is a very good choice for pattern recognition.
机译:在本文中,我们通过使用Ridgelets和傅里叶变换的组合来提出一种用于特征提取的新描述符。我们在包含图案的圆盘上成功地实现了循环磁盘上的脊髓,并在得到的ridgelet系数上应用了傅立叶变换,以提取用于模式识别的旋转不变特征。即使噪声水平高,描述符也非常强大地对高斯噪声。实验结果表明,新描述符是模式识别的非常好的选择。

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