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首页> 外文期刊>Journal of visual communication & image representation >Discriminative common vector based finger knuckle recognition
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Discriminative common vector based finger knuckle recognition

机译：基于区分公共向量的手指关节识别

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摘要

The main issue in personal authentication systems for military, security, industrial and social applications is accuracy. This paper presents a finger knuckle print (FKP) recognition approach to identity authentication. It applies a discriminative common vectors (DCV) based method to obtain the unique feature vectors, called discriminative common vectors, and the Euclidean distance as matching strategy to achieve the identification and verification tasks. The recognition process can be divided into the following phases: capturing the image; pre-processing; extracting the discriminative common vectors; matching and, finally, making a decision. In order to test and evaluate the proposed approach both the most representative FKP public databases and an established non-uniform FKP database were used. Experiments with these databases confirm that the DCV-based FKP recognition method achieves the authentication tasks effectively. The results showed the performance of the system in terms of the recognition rate had 100% accuracy for both training data and unseen test data.
机译：用于军事，安全，工业和社会应用的个人身份验证系统的主要问题是准确性。本文提出了一种用于身份认证的指关节指纹（FKP）识别方法。它采用基于判别性公共向量（DCV）的方法来获得唯一的特征向量，称为判别性公共向量，并以欧几里得距离作为匹配策略来实现识别和验证任务。识别过程可以分为以下几个阶段：捕获图像；预处理；提取有区别的公共向量；匹配，最后做出决定。为了测试和评估所提出的方法，使用了最具代表性的FKP公共数据库和已建立的非统一FKP数据库。这些数据库的实验证实，基于DCV的FKP识别方法可以有效地完成身份验证任务。结果表明，该系统在训练数据和看不见的测试数据方面的识别率均具有100％的准确性。

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