提出了一种对高斯模糊和高斯噪声鲁棒的图像纹理特征描述算子。

A novel image texture feature descriptor is proposed which is insensitive to Gaussian blur and Gaussian noise.

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通过人脸图片识别实验表明特征描述算子具有比lbp、LPQ等著名的特征描述算子具有更好的性能。

Experiment on face image recognition shows that the method has attractive features than LBP and LPQ which is the state-of-art local feature descriptors.

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人耳的角度变化和遮挡是人耳识别中的难点问题，SIFT局部描述算子具有对图像尺度缩放、平移、旋转等的不变性，因此提出利用SIFT特征的人耳识别算法。

The variety of ear angle and occlusion are the difficulties of ear recognition. The Scale Invariant Feature Transform(SIFT) is invariant to image scaling, translation and rotation.

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