6 boles w w , boashash b . a human identification technique usingimages of the iris and wavelet transform 掌纹可看成是由主线皱纹和乳突纹等基本构件形成的纹理图像。
Now , with this personal palm reader application is the palm of your other hand you can get a reading whenever you like 如今，有了这个掌纹解读软件你随时随地都可以查看掌纹！
2003 , 36 : 329 - 346 . 11 jain a , ross a , prabhakar s . an introduction to biometricrecognition . ieee trans 实验表明，各级小波能量特征对掌纹的区分能力由强到弱依次为第4 3 5 2和1级。
In present , most research of plamprint recognition is based on the feature of physics , structure or geometry 目前各种掌纹自动识别的研究主要是基于掌纹的物理、结构或几何特征。
Eigenpalms based feature extraction is designed according to the rule of in - class distance and between - class distance 基于特征手的掌纹特征提取算法是根据类内类间距离准则而设计的特征提取算法。
There are three modules in our capturing system , which are capture device module , pre - process module and the fusion module 本文实现的掌纹采集系统主要包括采集设备模块、预处理模块和图像融合模块。
Each kind of palmprint pattern is described by parameters in wavelet domain that learned form samples by estimation 通过样本学习，利用参数佑计的方法，每种掌纹模式的理想模型表示为小波域内的特定参变量。
Then , advance an algorithm for constructing the palm - line undirected graph according to the connection of the points on the palm - line 其次,根据掌纹线上各点的连结情况,提出一种掌纹线无向图的构建算法。
As one of the most important biometrics techniques , the development of palmprint recognition has a significant influence on real world 作为最重要的生物特征识别技术之一,掌纹识别方法的开发具有重要的现实意义。
As the crucial part of palmprint recognition , this paper mainly focuses on the ideas and usefulness and implementation of these two feature extraction algorithms 作为掌纹识别的关键部分,本文着重阐述两种特征提取算法的思想、作用和实现过程。
