Multispectral Palm Image Fusion for Person Authentication Using Ant Colony Optimization

D. Kisku, Phalguni Gupta, J. Sing, C. Jinshong Hwang
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引用次数: 20

Abstract

This paper presents an intra-modal fusion environment to integrate multiple raw palm images at low level. Fusion of palmprint instances is performed by wavelet transform and decomposition. To capture the palm characteristics, fused image is convolved with Gabor wavelet transform. The Gabor wavelet feature representation reflects very high dimensional space. To reduce the high dimensionality, ant colony optimization algorithm is applied to select relevant, distinctive and reduced feature set from Gabor responses. Finally, the reduced set of features is trained with support vector machines and accomplished user recognition tasks. For evaluation, CASIA multispectral palmprint database is used. The experimental results reveal that the system is found to be robust and encouraging while variations of classifiers are used. Also a comparative study is presented of the proposed system with a well-known method.
基于蚁群优化的手掌多光谱图像融合
提出了一种基于模态内融合的低水平多张原始掌纹图像融合环境。采用小波变换和分解方法对掌纹实例进行融合。为了捕捉手掌特征,对融合后的图像进行Gabor小波变换卷积。Gabor小波特征表示反映了非常高维的空间。为了降低高维数,采用蚁群优化算法从Gabor响应中选择相关的、独特的和简化的特征集。最后利用支持向量机训练约简后的特征集,完成用户识别任务。为了进行评价,使用了CASIA多光谱掌纹数据库。实验结果表明,当使用不同的分类器时,系统具有良好的鲁棒性和鼓舞性。并与一种已知的方法进行了比较研究。
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