| 基于ICA和BP神经网络的人耳图像识别 |
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| 引用本文： | 张海军,穆志纯,张成阳.基于ICA和BP神经网络的人耳图像识别[J].北京科技大学学报,2006,28(6):600-603. |
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| 作者姓名： | 张海军 穆志纯 张成阳 |
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| 作者单位： | 北京科技大学信息工程学院,北京,100083 |
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| 基金项目： | 国家高技术研究发展计划(863计划)
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北京市教委重点学科建设项目 |
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| 摘 要： | 提出了一种独立分量分析和BP神经网络相结合的人耳识别新方法(ICABP法).首先采用快速独立分量分析方法提取人耳图像的独立基图像和投影向量,然后采用改进的三层BP神经网络进行分类识别.该方法将ICA的空间局部特征提取功能和BP神经网络的自适应功能有机地结合起来,增强了系统的鲁棒性.实验表明,ICABP法取得了很高的识别率.
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| 关 键 词： | 人耳识别 独立分量分析 BP神经网络 特征提取 神经网络 图像识别 BP neural network independent component analysis based method 识别率 实验 鲁棒性 系统 增强 自适应 功能 特征提取 局部 空间 分类识别 改进 投影向量 基图像 |
| 收稿时间： | 2005-03-22 |
| 修稿时间： | 2005-09-09 |
Ear recognition method based on independent component analysis and BP neural network |
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| ZHANG Haijun,MU Zhichun,ZHANG Chengyang.Ear recognition method based on independent component analysis and BP neural network[J].Journal of University of Science and Technology Beijing,2006,28(6):600-603. |
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| Authors: | ZHANG Haijun MU Zhichun ZHANG Chengyang |
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| Institution: | Information Engineering School, University of Science and Technology Beijing, Beijing 100083, China |
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| Abstract: | A new ear recognition method combining independent component analysis (ICA) and BP neural network was proposed. The FastICA algorithm was used to derive independent basic images and projection vectors out of ear images, and three-layer BP neural network was used to classify ears. The local features extraction of ICA and the adaptability of BP neural network were combined reasonably. The robustness of the system was enhanced. Experiment results show that the ear recognition rate of the ICA-BP method is improved obviously. |
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| Keywords: | ear recognition independent component analysis BP neural network feature extraction |
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