针对姿态偏转时人耳图像识别率显著降低的问题，将局部切空间排列算法用于二维人耳特征的提取，提出一种局部切空间排列多姿态人耳识别方法。通过分析人耳图像的特点提出局部最大线性片构建策略，并以远少于样本点个数的局部切空间拟合样本集，再全局排列得到人耳低维流形。实验结果表明，该方法明显提高了姿态偏转下的识别率，并且计算效率得到改善，是一种有效的多姿态图像识别方法。%When ear posture varies greatly, the ear recognition rate decreases significantly. In this paper, a general recognition method based on local tangent space alignment is proposed to extract two-dimensional pose-invariant ear features. Unlike LTSA constructing local tangent space point by point, this method pre-sented a novel strategy to construct several overlapped local maximum linear patches to approximate the nonlinear multi-posed ear manifold. The number of the patches was far less than the total amount of dataset. Then these linear patches were aligned to obtain the corresponding lower dimensional manifold. The ex-perimental results on USTB ear database reveal that the proposed method can achieve better recognition per-formance and has less computation. It can be an effective multi-posed image recognition method.
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