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An Efficient Ear Recognition Method From Two-Dimensional Images

机译:来自二维图像的有效耳识别方法

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An efficient ear recognition method by weighted wavelet transformation and Bi-Directional principal component analysis was proposed. First, each ear image was decomposed into four sub-images by wavelet transformation ,the four sub-images were low frequency image , vertical detail image .horizontal detail image and high frequency image .Then the low frequency image was decomposed into four sub-images, the four-images were weighted by different coefficients, then ,the four sub-images were reconstructed into a image .On this basis ,the feature was extraction by the BDPCA method ,and then we use the k-Nearest Neighbor Classification to recognition .Experimental results show that the method have high recognition rate and shorted training time.
机译:提出了一种加权小波变换和双向主成分分析的高效耳识别方法。首先,通过小波变换将每个耳朵图像分解为四个子图像,四个子图像是低频图像,垂直细节图像。水平细节图像和高频图像。然后,低频图像被分解成四个子图像,四个图像被不同的系数加权,然后,将四个子图像重建为图像。该特征是由BDPCA方法提取的,然后我们使用K-Collect邻分类来识别。实验结果表明,该方法具有高识别率和短路训练时间。

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