虹膜纹理的英文

• iris marking

• "虹膜"英文翻译    iris; irides
• "纹理"英文翻译    vein; lines; stripes; grain; ...
• "和薄膜纹理" 英文翻译 :    film grain
• "粘膜纹" 英文翻译 :    mucosal relief; mucosal striation
• "纹理" 英文翻译 :    vein; lines; stripes; grain; graining; varvity; texture◇纹理方向 grain direction
• "虹膜" 英文翻译 :    [生理学] iris; irides◇虹膜固定术 iridodesis; iridesis; iridosis; 虹膜镜 iridoscope; 虹膜切除术 iridectomy; 虹膜切开术 irotomy; 虹膜炎 iritis
• "视网膜纹" 英文翻译 :    retinae striae; stria retinae
• "线状粘膜纹" 英文翻译 :    linear mucosal striation
• "弹簧状粘膜纹" 英文翻译 :    spring-like mucosal pattern
• "薄纹理" 英文翻译 :    fissile bedding
• "粗纹理" 英文翻译 :    coarse grain; open grain
• "肺纹理" 英文翻译 :    lung makings; lung marking; lung-markings; pulmonary markings
• "革纹理" 英文翻译 :    leather grain
• "横纹理" 英文翻译 :    across grain
• "脉络；纹理" 英文翻译 :    venation
• "年纹理" 英文翻译 :    a ual lamination; annual lamination
• "平纹理" 英文翻译 :    flat grain
• "顺纹理" 英文翻译 :    with the grain
• "条痕；纹理" 英文翻译 :    streak
• "突纹理" 英文翻译 :    raised grain
• "微纹理" 英文翻译 :    microlamination
• "纹理；粒" 英文翻译 :    grain
• "纹理层" 英文翻译 :    texture layer
• "纹理带" 英文翻译 :    striated band
• "纹理点" 英文翻译 :    texture noise

• Calibration algorithm for center deviation of circles for iris normalization
  虹膜纹理归一化的圆心偏差校正算法
• By means of the mathematical properties of cl multiwavelet , the iris texture feature can be presented accurately and primely
  利用cl多小波优良的数学性质，虹膜纹理特征能够被准确完整地表达。
• Iris identification is based on iris texture to identify persons , and it is one of most accurate biometrics technologies
  虹膜识别是基于人眼虹膜纹理特征来确定人的身份的一种识别方法,也是最为准确的生物特征识别方法之一。
• ( 3 ) a previous way of iris feature extraction based on gaussian - hermite moment is studied and applied in this paper , and the imfluences of some important parameters are explained
  3 .研究了gaussian - hermite矩的滤波特性,并参照已有的利用gaussian - hermite矩提取虹膜纹理特征的方法,用此方法对虹膜信号进行特征提取,同时,说明了各类参数对识别结果的影响。
• Then the exisiting algorithms on iris location are studied and the disadvantages are pointed . a new approach based on edge detection , mathematic morphology and probability statistic is put forward . after studing the means of daugman ’ s encode of iris texture and w . w . boles ’ extraction the unique features by the zero - crossings of the wavelet transform , we adopted wavelet multi - resolution analysis that extract the feature
  在研究和分析了前人的虹膜定位算法以及daugman对虹膜纹理的编码方法、 w . w . boles的小波过零点分析提取虹膜特征识别算法的基础上,研究了基于边缘检测和数学形态学以及概率统计等理论的一种新的虹膜定位方法;研究了虹膜图像的归一化和图像增强;研究了基于db4小波的多分辩率分析的虹膜特征提取算法;研究了相关系数匹配识别。
• Such recognition algorithms the feature extraction based on a set of 2 - d gabor wavelet and computation of percentage mismatched bits hamming distance between a pair of iris representations developed by daugman , texture analysis methods developed by wildes and chinese academy of science , extraction of iris signatures by means of zero - crossing of the dyadic wavelet transform developed by boles and so on
  深入研究了多种典型识别算法: daugman的基于2 - d复值gabor小波的虹膜相位编码和hamming距离的方法; wildes和中科院的基于虹膜纹理分析的方法; boles的基于小波过零检测的方法;上海交大的基于小波模极大值的方法等。并在此基础上,对虹膜识别系统中的图像预处理和识别的若干算法进行了改进。
• Due to the unique , stable and live physiological properties of the iris and non - invasive to users , most stable and reliable for identification in practical applications of iris - based system , iris recognition is receiving extensive attention and becoming an active topic in biometrics . as an application - oriented research project , iris recognition integrates mathematic , computer science , optics , electronics and physiology etc . based on wavelet transform , aimed to improve the recognition performance , centered at wavelet - based iris feature representation and pattern classification , we review and explore the iris sequence image quality assessment , iris image pre - processing , iris recognition performance evaluation and several other linked topics . we mainly investigate on the principles and application methodology of wavelet transform for iris feature representation and iris pattern classification methods
  以小波变换技术为基础,结合图像处理和模式识别方法,设计并开发了虹膜图像采集装置,建立了虹膜识别算法测试实验平台;重点研究了虹膜识别中的小波变换的应用基础理论与关键实现技术;提出了基于小波局部模极大值的虹膜特征表示及其多重匹配识别、基于小波多尺度信息的一维和二维虹膜纹理特征量化表示、基于小波过零点技术的虹膜特征表示及其规范化的部分hausdorff距离匹配识别,这三类方法能够有效地提取虹膜特征;基于自建的算法测试平台,对上述三类方法和其他三种国内外比较有影响的基于小波变换的虹膜识别方法进行了定量的性能比较和评价,通过实验数据分析得到了有意义的结论;最后指出了小波变换技术在虹膜识别领域的研究重点与发展方向。
• While in the feature extraction , four ways are researched such as the means of encode of iris texture , the improved algorithm based on daugman ' s , the approach of identification by means of the fourier spectra of the transmission binary model of the human irises and the method of iris identification using wavelet transform . the advantages and disadvantages of these ways are compared . improved algorithm based on wavelet transform is proposed and proves feasible
  虹膜定位中既分析了前人的一些算法，指出算法中的不足，又结合数学形态学和hough变换等理论提出两种新的虹膜定位方法；虹膜特征提取算法中，研究了daugman对虹膜纹理的粗量化和编码，康浩等在daugman基础上的改进算法， muron等人的利用虹膜二元模型的傅立叶光谱分布特征进行识别以及boles的基于小波变换的虹膜识别算法等，比较出各个算法的优缺点，并且在boles的研究基础上进行了改进，经实验证明该方法可行。