论文编号:TX267  论文字数:19729,页数:53，有开题报告，任务书，源码

摘 要
　
 近几年，随着生物特征识别技术的发展以及人们对自身隐私、财产安全的日益关注，生物特征识别技术在越来越多的场合得到应用。相对于传统的指纹、虹膜识别技术、掌纹识别技术是一个新兴的领域。掌纹识别技术具有采样设备简单，信息量大的优点，受到了广泛的关注。
 本文对这一研究课题展开了初步的论述，介绍了掌纹识别技术研究的背景与国内外掌纹识别技术的发展情况。然后介绍了掌纹识别的方法和流程，包括掌纹图片数据的采集、对掌纹图像的预处理，对掌纹数据进行特征提取、进行分类识别和匹配。之后对掌纹识别算法进行了研究，首先是通过基于K-L离散变换对掌纹数据进行特征提取，其次是利用神经网络里的误差回传神经网络（BP）算法对提取的数据进行分类识别。最后运用MATLAB制作了掌纹识别的GUI界面，通过利用MATLAB编程语言进行程序的设计以最终达到掌纹识别的目的，并通过界面来展现出来。
 
关 键 词：生物特征识别,掌纹识别,离散K-L变换,神经网络,特征提取，分类识别
 
  SOFTWARE DESIGN OF PALMPRINT RECOGNITION

ABSTRACT
 
   
 In recent years, with the development of biometrics recognition technology and the increasing attention to privacy and personal safety of people, biometrics recognition technology is used more and more widely in different occasions. Compared with fingerprint recognition and iris recognition, palmprint recognition is a newly developed field during the past several years. Palmprint contains more information than other biometrics features and can be collected by simpler device, so more and more people are entering this field.
 In this paper, the topic was discussed preliminary. At the same time, the background of palmprint recognition technique and the domestic and international development of palmprint recognition technique was discussed too. Then the methods and processes of palmprint recognition technique was described in this paper, including the collection and pretreatment of palmprint images , feature extraction, classification recognition and match of palmprint images database. After the text discussed the way of the palmprint identify calculation. Firstly, the feature was extracted which was based on discrete K-L transformation. Secondly, Back-Propagation Neural Network(BP) was used to recognize the feature which was extracted from the database. Finally GUI interface which was used to recognizing palmprint was produced by using MATLAB and MATLAB edit language to editing procedure for the purpose of palmprint recognition. The result was displayed in GUI interface.

KEY WORDS: biometrics recognition, palmprint recognition, discrete K-L transformation, neural network, feature extraction, classification recognition

目  录

前  言 1
第1章 研究背景和意义 3
 1.1 背景介绍 3
 1.2 生物特征识别技术的市场前景 4
 1.3 不同种类的生物特征识别技术竞争发展 5
 1.4 掌纹识别技术 7
 1.4.1 掌纹相关概念  7
 1.4.2 掌纹识别技术的特点  8
第2章 掌纹识别的方法流程 9
 2.1 掌纹识别方法流程概述 9
 2.2 掌纹识别方法流程介绍 10
 2.2.1 掌纹图像的采集 10
 2.2.2 掌纹图像的预处理  10
 2.2.3 掌纹数据的特征提取  10
 2.2.4 掌纹数据的分类识别  16
第3章 用户界面设计 24
 3.1 用户界面设计概述 24
 3.2 用户界面设计流程  24
 3.3 掌纹识别的实现  24
第4章 使用说明书 27
第5章 测试分析报告 29
第6章 项目开发总结 31
结论 33
参考文献 34
致　谢 36
附　录 37

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