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A Real Time Fingerprint Identification System Based On The Afs8600 Sensor And The C6713 Dsp Processor

机译:基于Afs8600传感器和C6713 Dsp处理器的实时指纹识别系统

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In this paper, a fingerprint pre-process and identification algorithm is implemented using the TMS320C6713 DSP starter kit (DSK) module, along with the Authentee AFS 8600 fingerprint sensor. Database: Acquisition is performed using a solid stale sensor. The sensor postulates emerge from the theory of the Electric Field technology. Method: Images are first subjected to a frequency and orientation processing. This is achieved using Gabor-based filters. This processing has been optimized and implemented on the DSP system. A new method has been developed in order to extract the feature vector of the fingerprint image A grid, centered at the core-rnpoint of the image, is applied to the fingerprint image in order to derive local information. Classification algorithms are developed, which include training as well as evaluating phase. The types of classifiers used were based on the Bayesian approach along with the K-nearest neighbour. Results: An identification accuracy of 90% was achieved which is comparable to other procedures described in the literature. Conclusion: The combination of a fingerprint processing and identification algorithm using a low cost sensor and DSP module has been presented.
机译:本文使用TMS320C6713 DSP入门工具包(DSK)模块以及Authentee AFS 8600指纹传感器实现了指纹预处理和识别算法。数据库:使用固态传感器进行采集。传感器假设来自电场技术的理论。方法:首先对图像进行频率和方向处理。这是使用基于Gabor的滤波器实现的。此处理已优化并在DSP系统上实现。为了提取指纹图像的特征矢量,已经开发了一种新方法。将以图像的核心点为中心的网格应用于指纹图像,以导出局部信息。开发了分类算法,其中包括训练以及评估阶段。使用的分类器类型基于贝叶斯方法以及K近邻。结果:达到了90%的识别准确度,可与文献中描述的其他程序相媲美。结论:提出了使用低成本传感器和DSP模块的指纹处理和识别算法的组合。

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