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Palmprint Based Recognition System Using Local Structure Tensor and Force Field Transformation

机译:基于局部张量和力场变换的掌纹识别系统

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This paper presents an efficient palmprint based recognition system. In this system, the image is divided into disjoint sub-images. For each sub-image, the dominant orientation pixels based on the force field transformation are identified. Structure tensor values of these dominant orientation pixels of each sub-image are averaged to form tensor matrix for the sub-image. Eigen decomposition of each tensor matrix is used to generate the feature matrix which is used to take decision on matching. The system has been tested on IITK database. The experimental results reveal the accuracy of 100% for the database.
机译:本文提出了一种有效的基于掌纹的识别系统。在该系统中,图像分为不相交的子图像。对于每个子图像,基于力场变换识别主导方向像素。将每个子图像的这些主要取向像素的结构张量值平均以形成子图像的张量矩阵。每个张量矩阵的特征分解用于生成特征矩阵,该特征矩阵用于做出匹配决策。该系统已经在IITK数据库上进行了测试。实验结果表明该数据库的准确性为100%。

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