摘要
由于不同人的手背静脉属性间存在较大差异,因此对于不同静脉对象,在固定采集系统参数条件下很难都采集到高质量的静脉图像,这里提出了一种针对静脉特点的质量评价模型,并设计了基于评价结果的自寻优静脉图像采集方法.首先,提出了基于关键信息熵的测度函数,衡量了静脉信息的完整性;其次,提出了基于轮廓波分解的测度函数,用于评价静脉方向性信息的丰富性;再次,将两种测度函数融合,构成了客观的无参考的质量评价模型;最后,在图像自寻优过程中,提出了迭代淘汰机制,克服了最速下降法在寻优过程易陷入局部最优的缺陷.实验表明,提出的质量评价模型是可控的,且满足人眼视觉系统的视觉特性,同时,通过提出的迭代淘汰机制,降低了寻优过程的迭代次数,保证了采集系统的实时性要求.
Because of dorsal vein properties difference between different persons,for different vein objects not all vein images with high qualities can be acquired when fixing acquisition system parameters,in the paper a newimage quality assessment model is proposed according to vein characteristics,moreover,vein image can be acquired through self optimization based on assessment result. First,a measure function based on key information entropy is proposed,which measures vein information completeness; Second,another measure function based on Contourlet decomposition is proposed,which is used to judge whether vein directional information is rich or not; Third,the objective vein image quality assessment model without reference is formed by fusing the two measure functions. In final,iteration elimination method is proposed in order to overcome the defect of steepest descent method,which is easy to fall into local optimum during optimization process. Experiments showthe proposed quality assessment model is controllable and can meet the characteristics of human visual system,in the meantime the number of iterations can be reduced effectively through the proposed iteration elimination method,and the real-time requirement of acquisition system can be ensured.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2015年第2期236-241,共6页
Acta Electronica Sinica
基金
辽宁省教育厅一般项目(No.L2013241)
国家自然科学基金(No.61272214)
关键词
静脉采集
质量评价
最速下降法
轮廓波分解
vein acquisition
quality assessment
steepest descent method
contourlet decomposition
