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A Method of Dorsal Hand Vein Identification

机译:背手静脉识别方法

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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:提出了一种从手背静脉(DHV)图像提取全局Gist特征的新算法,以克服现有算法中细节缺失静脉结构和特征点误判的缺陷。采用通用的生物特征识别过程,通过图像灰度归一化预处理和滤波增强对手背静脉图像进行处理后,提取出DHV灰度图像的全局Gist特征作为纹理特征。然后通过应用K.近邻分类器来识别个人身份。最后,通过使用自建的背静脉图像数据库对该算法进行了验证。实验结果表明,该算法是有效的,正确识别率为96.7%,具有广阔的应用前景。

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