Ear recognition method based on independent component analysis and BP neural network
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摘要: 提出了一種獨立分量分析和BP神經網絡相結合的人耳識別新方法(ICABP法).首先采用快速獨立分量分析方法提取人耳圖像的獨立基圖像和投影向量,然后采用改進的三層BP神經網絡進行分類識別.該方法將ICA的空間局部特征提取功能和BP神經網絡的自適應功能有機地結合起來,增強了系統的魯棒性.實驗表明,ICABP法取得了很高的識別率.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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Key words:
- ear recognition /
- independent component analysis /
- BP neural network /
- feature extraction
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