摘要
Contourlet变换不同子带的特征提取能力存在差异。针对该问题,提出一种基于能量补偿和特征加权的虹膜特征提取算法。采用正交图像对原图像进行能量补偿,利用广义高斯分布估计各子带数据的权值,为分类能力强的特征量赋予较大权值,以充分使用样本的统计信息高效地提取特征。实验结果表明,该算法的虹膜识别率较高,鲁棒性较强。
This paper proposes an iris feature extraction algorithm based on energy compensation and feature weighting to solve the problems that the capacities of the feature extraction with different sub-band of the Contourlet transformation are different.It uses orthogonal images to achieve energy compensation for the original images,estimates the weights of sub-bands by using General Gaussian Distribution（GGD）,and gives larger weight for the feature with better classification capacity,so that the statistical information of the samples is made full use of and the features are extracted efficiently.Experimental results show that the algorithm has good robustness and improves iris recognition rate.
出处
《计算机工程》
CAS
CSCD
2012年第1期165-167,共3页
Computer Engineering
基金
陕西省自然科学研究计划基金资助项目(2010JK740
2010JM8019)
西安市科学技术局基金资助项目(CXY08017(2))
2009年度西安理工大学学科联合研究基金资助项目(102-210914)
关键词
CONTOURLET变换
虹膜特征提取
能量补偿
特征加权
广义高斯分布
Contourlet transformation
iris feature extraction
energy compensation
feature weighting
General Gaussian Distribution（GGD）
