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Palmprint Recognition Based on Curvelet Transform Decision Fusion

机译:基于Curvelet变换决策融合的Palmprint识别

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Curvelet transform is a multi-scale method that can represent curves most sparsely. The main feature of palmprint images is that it is made up of several main curves. This paper utilizes the curvelet transform to extract the feature information of palmprint images on different scales, deals with the information by dimension reduction of PCA(Principal Component Analysis), then provides the information for RBF network to study and make decisions. Finally, according to the customers' requirements, this paper chooses decision rules to get the fusion of the results and attain the goal of palmprint recognition. It has been proved by the experiments that this method can fully make use of the features information of images and can obtain higher recognition rate than other methods
机译:Curvelet变换是一种多尺度方法,可以最稀疏地表示曲线。 PalmPrint图像的主要特征是它由几种主要曲线组成。本文利用Curvelet变换来提取不同尺度上PalmPrint图像的特征信息,通过PCA的维度减少来处理信息(主成分分析),然后为RBF网络提供学习和做出决策的信息。最后,根据客户的要求,本文选择了决策规则,以获得结果的融合并实现掌纹认可的目标。通过实验证明,该方法可以充分利用图像的特征信息,并且可以获得比其他方法更高的识别率

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