Implementation and Analysis of Novel Iris Monitoring System using Prewitt Algorithm in comparing with Sobel Algorithms by Signal-to-Noise Ratio

D. R. D. Varma, R. Priyanka
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引用次数: 0

Abstract

The novel performance analysis of prewitt algorithm for iris monitoring in comparison with the sobel to improve the Signal to Noise Ratio (SNR) for improving strength of the signal using. Materials and Methods: The 40 samples were collected using the g power clinical calculator. G1 as the prewitt algorithm with 20 samples and g2 as the sobel algorithm with 20 samples. 80% of power is prescribed for pretest and the acceptable error of 0.05 were used to identify the number of samples. Results: The prewitt algorithm has achieved the predominant performance accuracy of 94.0% when compared to the sobel algorithm with 87.85% of accuracy. The prewitt algorithm has the implication of ($\mathrm{p} < 0.05$) with the sobel algorithm. Conclusion: The prewitt algorithm is implified greater accuracy when compared with the sobel algorithm.
基于Prewitt算法的新型虹膜监测系统的实现与分析,并通过信噪比与Sobel算法进行比较
分析了新颖的prewitt算法用于虹膜监测的性能,并与sobel算法进行了比较,以提高信号的信噪比(SNR),用于提高信号的强度。材料与方法:采用g功率临床计算器采集40例标本。G1为20个样本的prewitt算法,g2为20个样本的sobel算法。规定80%的功率进行预测,采用0.05的可接受误差来识别样本数。结果:prewitt算法的准确率为94.0%,sobel算法的准确率为87.85%。prewitt算法与sobel算法具有($\mathrm{p} < 0.05$)的含义。结论:与sobel算法相比,prewitt算法具有更高的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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