基于自回归模型估计小波系数的掌纹验证

Fereshte Yazdani, M. E. Andani
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引用次数: 4

摘要

生物识别是一种根据人的生理和行为特征自动识别人的模式识别系统。在生理特性中,手具有特殊的地位,手的掌纹、内指关节、外指关节、几何形状等所有特征都可以被运用。最近,手掌血管图案的使用,除了具有较高的可接受性外,由于与手掌相比具有更高的独特性和耐久性,因此被研究人员考虑。本文采用基于自回归模型的小波系数估计方法提取纹理特征进行验证。利用支持向量机和k近邻分类器的新方法对50个人的600张手掌图像进行特征分类,最终得到错误率和准确率相等的评价结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Verification based on palm vein by estimating wavelet coefficient with autoregressive model
Biometric is a pattern recognition system that automatically identifies people according to their physiologic and behavioral properties. Among the physiologic properties, hand has a special place so that all features of hand like palm lines, inner knuckles, external knuckles and geometry could be used. More recently, the usage of blood vessels pattern in the palm, in addition to the high acceptability, is considered by researchers due to the higher uniqueness and durability in comparison to the palm. In this article, the new method based on the estimate of wavelet coefficient with autoregressive model is used to extract the texture feature for verification. The features from the 600 palm images captured from 50 individuals are classified by the new methods of support vector machine and K-nearest neighbor classifier and eventually results in evaluation with equal error rate and Accuracy standards.
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