特征搜索算法在图书馆指纹识别系统中的应用

Tuofu Peng
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引用次数: 0

摘要

指纹识别作为一种重要的身份识别方法,有着广泛的应用前景。为了提高图书馆指纹识别系统的效率和安全性,提出了一种基于特征搜索算法的识别技术,并对该算法的性能进行了分析。当设置合理的阈值时,可以将算法的匹配错误率控制在较低的水平,同时算法也可以保证较高的指纹,确定整体的准确率。同时介绍了射频指纹识别、卷积神经网络和局部二值模式三种同类型的识别算法。在对比实验中,发现特征搜索算法模型的准确率最高,达到94.8%。在处理相同数量的指纹数据时,该算法模型的识别时间最短。此外,该算法的接收者工作特征曲线对应的曲线值下面积最大,其值为0.94。众所周知,特征搜索算法的性能是最优的,可以有效地提高图书馆指纹识别系统的运行效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using the characteristic search algorithm in a library fingerprint identification system
As an important identification method, fingerprint recognition has a wide range of applications. To make the fingerprint recognition system of a library more efficient and secure, a recognition technology based on the characteristic search algorithm is proposed, and the performance of the algorithm is analysed. When a reasonable threshold is set, the matching error rate of the algorithm can be controlled at a lower level, and the algorithm can also ensure a higher fingerprint and determine the overall accuracy. At the same time, three other identification algorithms of the same type are introduced: radio frequency fingerprinting, convolutional neural network and local binary pattern. In a comparative experiment, it was found that the characteristic search algorithm model had the highest accuracy, with a value of 94.8%. When dealing with the same amount of fingerprint data, the recognition time of the algorithm model was the shortest. In addition, the area under the curve value corresponding to the receiver operating characteristic curve of the algorithm was the largest, and its value was 0.94. It is well known that the performance of the characteristic search algorithm is optimal and can effectively improve the operation efficiency of a library fingerprint identification system.
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CiteScore
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