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A method of dorsal hand vein identification

机译:一种背部手静脉识别方法

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A novel algorithm of global Gist feature extraction from Dorsal Hand Vein (DHV) image was proposed in order to overcome the defects of losing vein structure in details and the misjudgment of feature points in the existing algorithms. Adopting general biometric identification process, the global Gist features of the DHV gray image is extracted as the texture features after the dorsal hand vein image is reprocessed by image gray normalization pretreatment and filtering enhancement. And then the personal identity was recognized by applying K neighbor classifier. This algorithm was finally verified by using self-established dorsal vein image database. The experimental results show that the proposed algorithm is effective and its correct recognition rate is 96.7%, and so the application prospect is broad employed.
机译:提出了一种来自背部手静脉(DHV)图像的全局GIST特征提取算法,以克服现有算法中的细节中损失静脉结构的缺陷和误判。采用一般的生物识别过程,通过图像灰色归一化预处理和过滤增强,将DHV灰度图像的全局GIST特征作为纹理特征提取为纹理特征。然后通过应用K邻居分类器来识别个人身份。最后通过使用自建立的背静脉图像数据库来验证该算法。实验结果表明,该算法有效,其正确的识别率为96.7%,因此应用前景广泛使用。

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