Subsampling Based Neighborhood Preserving Embedding for Image Classification

Li-Yan Zhao, Dong Zou, Guanghong Gao
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引用次数: 3

Abstract

In this paper, a novel image feature extraction algorithm, called Subsampling based neighborhood preserving embedding (SNPE), is proposed. SNPE aims to preserve the neighborhood of the subsampling image samples. The proposed algorithm is applied to image classification on Finger-Knuckle-Print database. The experimental results confirm the effectiveness of the proposed algorithm.
基于子采样的邻域保持嵌入图像分类
提出了一种新的图像特征提取算法——基于子采样的邻域保持嵌入算法(SNPE)。SNPE的目的是保持子采样图像样本的邻域。将该算法应用于指关节指纹数据库的图像分类。实验结果验证了该算法的有效性。
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