基于Gabor相位和图像质量评价的高分辨率掌纹细节点提取算法  

High-Resolution Palmprint Minutiae Extraction Based on Gabor Phase and Image Quality Estimation

作　　者：刘重晋[1] 王瀚[1] 封举富[1] 

机构地区：[1]北京大学信息科学技术学院智能科学系机器感知与智能教育部重点实验室,北京100871

出　　处：《北京大学学报（自然科学版）》2015年第3期384-390,共7页Acta Scientiarum Naturalium Universitatis Pekinensis

基　　金：国家自然科学基金(61333015);国家重点基础研究发展计划(2011CB302400)资助

摘　　要：针对主线、褶皱线及噪声等造成高分辨率掌纹细节点提取困难的问题,提出一种基于Gabor相位和图像质量评价的高分辨率掌纹细节点提取算法。首先使用Gabor振幅相位模型对掌纹图像进行描述,并基于Gabor相位提出多尺度的细节点检测方法;然后利用提取细节点过程中的信息,设计基于傅里叶响应的质量评价方法和基于Gabor振幅的质量评价方法;最后融合两种质量评价结果,并对检测到的细节点进行筛选。实验结果表明,所提方法能够有效地提取高分辨率掌纹图像的细节点,并去除不可信细节点。与其他方法相比,具有更好的细节点提取结果。Extracting minutiae is difficult for high-resolution palmprint because of the strong influence from principal lines, creases and other noises. A novel high-resolution palmprint minutiae extraction method is proposed based on Gabor phase feature and image quality estimation. Firstly, the Gabor amplitude-phase model is introduced for palmprint representation. Based on the obtained Gabor phase, a multi-scale minutiae detection method is proposed. Then with the information from minutiae detection, the authors design Fourier response based quality estimation method and Gabor amplitude based quality estimation method. Finally, the two image quality estimation results are fused for minutiae screening to remove the unreliable minutiae. Experiment results show that the proposed method can extract minutiae effectively from high-resolution palmprint and remove the unreliable ones. Compared with other methods, the orooosed method obtains better minutiae extraction results.

关 键 词：掌纹识别 细节点提取 图像质量评价 Gabor卷积 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]