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作 者:吴明珠 陈瑛 李兴民[2] Wu Mingzhu;Chen Ying;Li Xingmin(College of Information Engineering,Guangzhou Institute of Technology,Guangzhou 510075,China;School of Computer Science,South China Normal University,Guangzhou 510631,China)
机构地区:[1]广州工程技术职业学院信息工程学院,广州510075 [2]华南师范大学计算机学院,广州510631
出 处:《计算机应用研究》2020年第4期1276-1280,共5页Application Research of Computers
基 金:2017年重点平台及科研项目特色创新类项目(自然科学)(2017GKTSCX049,2017GKTSCX050)。
摘 要:针对目前掌纹识别算法中对彩色掌纹图像的识别研究不多,提出一种新的基于Stein-Weiss函数解析性质的BP神经网络彩色掌纹图像的识别算法。首先为彩色掌纹图像中的每个像素点构建一个Stein-Weiss函数,再根据Stein-Weiss函数的解析性,计算出相应像素的16个特征值,将这些特征值输入到BP神经网络的输入层,通过BP神经网络的自学习能力对这些数据进行分类学习;然后通过BP神经网络的泛化能力来获取掌纹边缘线;最后对掌纹边缘线提取成对几何特征建立特征库,通过成对几何直方图相交算法进行掌纹识别。实验结果表明,相对于以往的灰度掌纹图像识别算法,该算法能够更快地提取出更精细的掌纹线,识别率更高,并且对于旋转和噪声的干扰具有较强的鲁棒性。For the problem of the palmprint recognition algorithm had less research on the recognition of color palmprint images,this paper proposed a new BP neural network color palmprint image recognition algorithm based on the analytical properties of Stein-Weiss function.The proposed method firstly constructed a Stein-Weiss function for each pixel in the color palmprint image.Then according to the analyticity of the Stein-Weiss function,it calculated sixteen eigenvalues of the corresponding pi-xel,and used these eigenvalues as the input data of the BP neural network.These data could be classified and learned through the self-learning ability of BP neural network.Then it obtained the palmprint edge through generalization ability of BP neural network.Finally,it extracted the pairwise attributes from palmprint edge,and built the feature library.The palmprint was recognized by the paired geometric histogram intersection algorithm.The experimental results show that the proposed algorithm can extract finer palmprint faster and the recognition rate is higher compared with the previous grayscale palmprint image recognition algorithms.And it has strong robustness to the interference of rotation and noise.
关 键 词:Stein-Weiss函数 解析性 反向传播神经网络 掌纹识别 成对几何特征 鲁棒性
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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