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用于掌纹识别的多顺序扩展码

Fengxiang Liao¹, Lu Leng¹, Ziyuan Yang²

¹Jiangxi Province Key Laboratory of Image Processing and Pattern Recognition, Nanchang Hangkong University, 696 Fenghe Nan Avenue, Nanchang, 330063 Jiangxi, P. R. China.

International journal of neural systems

|July 7, 2025

概括

本研究介绍了手掌纹识别的多级扩展,包括一级和二级纹理特征 (1TF和2TF). 这种新的方法显著提高了手掌纹纹理编码方法的准确性,以改善生物识别.

科学领域:

生物识别和模式识别技术
计算机视觉计算机视觉
图像处理图像处理

背景情况:

掌纹识别是具有许多应用的关键生物识别模式.
目前的方法主要使用一级纹理特征 (1TFs),忽视有价值的二级纹理特征 (2TFs).
加博尔过器是神经系统启发的有效的纹理提取器.

研究的目的:

建议对现有的手掌纹纹理编码方法进行多级扩展.
为了提高识别,利用一级纹理特征 (1TFs) 和二级纹理特征 (2TFs) 的优势.
建立基于纹理的识别任务的一般框架.

主要方法:

建议为手掌纹纹理编码提供一个多顺序的扩展框架.
使用过器提取一级纹理特征 (1TFs).
第二阶段的纹理特征 (2TFs) 通过使用相同的过器从1TFs中提取出来,过器对不同的纹理有所变化.

主要成果:

多订单扩展框架有效利用1TF和2TF.
1TFs和2TFs同时参与代码导致更具歧视性的特征提取和融合.
实验结果显示,在三个公共数据库 (接触式,非接触式,多谱式) 中,准确度显著提高.

结论:

多序扩展显著提高了手掌纹纹理编码方法的准确性.
拟议的框架提供了一种可通用的方法,适用于其他基于纹理的识别任务.
这种方法为生物识别提供了更强大和更具歧视性的特征集.

关键词:

生物识别识别的生物识别功能多订单扩展多订单扩展掌印识别功能掌印识别功能第二阶段的纹理特征是第二阶段的纹理特征.

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