| 基于非负稀疏编码和RBPNN的掌纹图像识别方法 |
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| 引用本文： | 尚丽,CHEN Jie.基于非负稀疏编码和RBPNN的掌纹图像识别方法[J].苏州市职业大学学报,2008,19(1):65-69. |
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| 作者姓名： | 尚丽 CHEN Jie |
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| 作者单位： | 苏州市职业大学,电子信息工程系,江苏,苏州,215104 |
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| 摘 要： | 主要探讨了一种新颖的基于非负稀疏编码（NNSC）和径向基概率神经网络（RBPNN）模型的掌纹图像识别方法。使用NNSC算法可以成功地提取掌纹图像的特征，利用RBPNN模型可以有效、快速地实现掌纹图像的分类。与RBFNN和BPNN模型相比，实验结果表明RBPNN模型具有更高的识别率和更好的分类能力。
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| 关 键 词： | 非负稀疏编码(NNSC) 径向基概率网络(RBPNN) 掌纹图像 图像识别和分类 |
The Method of Palmprint Recognition Based on Non-negative Sparse Coding and Radial Basis Probabilistic Neural Network |
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| SHANG Li,CHEN Jie.The Method of Palmprint Recognition Based on Non-negative Sparse Coding and Radial Basis Probabilistic Neural Network[J].Journal of Suzhou Vocational University,2008,19(1):65-69. |
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| Authors: | SHANG Li CHEN Jie |
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| Institution: | (Suzhou Vocational University, Suzhou 215104, China) |
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| Abstract: | The paper mainly discusses a novel palmprint recognition method based on Non-negative Sparse Coding （NNSC） and Radial Basis Probabilistic Neural Network （RBFNN）. Palmprint features can be extracted successfully by using the algorithm of NNSC, and the classification task can be implemented efficiently and fast by the RBPNN model proposed. Moreover, compared with the classification methods of Radial Basis Function Neural Network（RBFNN） and BPNN, experimental results also show that the RBPNN achieves higher recognition rate and better classification efficiency. |
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| Keywords: | Non-negative Sparse Coding （NNSC） Radial Basis Probabilistic Neural Network （RBPNN） palmprint images image recognition and calssification |
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