针对局部线性嵌入(LLE)算法易受偏转角度和近邻选取的影响，提出了一种双层LLE(DLLE)的人耳图像识别方法，并结合Gabor小波和DLLE提出了GDLLE。DLLE首先计算各样本与每类样本中心的欧氏距离，再把欧氏距离最小的K类所有样本作为LLE的近邻，提取出鉴别特征，最后由最近近邻分类器对鉴别特征进行分类。在USTB3人耳图像库上的实验结果表明，本文提出DLLE能够减小偏转角度和近邻对LLE算法的影响，结合Gabor小波后进一步改善了算法的识别率。

As LLE algorithm is apt to be influenced by the deflection angle and the selection of the proximal points, a method of Double-layer LLE (DLLE) human ear recognition is put forward. And a further algorithm combined with Gabor is proposed with the name of GDLLE (Gabor and DLLE). The DLLE algorithm calculate the Euclidean distance between sample point and the center of the sample points first, then take all of the K-class sample points whose Euclidean distance are the minimum as neighbor points of LLE, extract the discriminate features, and classify them by the nearest neighbor classifier finally. The experiments on USTB3 ear image database reveal that the DLLE method proposed in this paper can reduce the impacts of the deflection angle and the selection of the proximal points on LLE algorithm, and recognition rate is further improved with the combination of Gabor wavelet.