基于图像处理的心音图特征提取技术的研究

研究生签名：____________ 导师签名：_______ห้องสมุดไป่ตู้____ 日期：_____________
摘要
在数学上可以通过作图帮助解决一些抽象的问题，将抽象的问题具体图形化可以帮助理 解问题的本质。心音信号是人体最重要的生理信号之一，对它进行图形化可以将抽象的声音 信号转换成人们更善于理解的波形图像。论文中二维心音图概念就是基于这样的理念诞生。 二维心音图可以真实地记录正常心音、额外心音以及心脏杂音。在医学上，二维心音图和心 脏听诊同时运用可以取长补短。在生理信息方面，二维心音图包含丰富的个人生理信息，如 个人健康信息和身份信息等。 图像处理技术经过多年的快速发展，已经趋于成熟。论文首先运用一维信号处理方法对 心音信号进行小波降噪和幅值归一化，将处理后的心音转换成具有统一性和可比性的标准二 维心音图。接着运用图像处理技术对二维心音图进行预处理，包括灰度化、背景归一化、二 值化、细化操作。然后结合心音的生理意义和二维心音图图像特征，对能表征二维心音图生 理信息的图像特征进行分析研究，重点研究了二维心音图纵横坐标比和拐点序列码特征。其 中，纵横坐标比是将一维心音幅值时间比的生理健康信息转换成二维图像后提出来的；拐点 序列码是将一维心音双峰子波、三峰子波、四峰子波概念转换成二维图像后提出来的，它能 表征身份信息唯一性的细节特征。小波分解系数特征是小波分解得到图像整体轮廓的低频系 数矩阵和图像细节的高频系数矩阵的组合特征参数。 最后，基于纵横坐标比、拐点序列码、小波分解系数三个特征，分别探讨了利用欧式距 离和支持向量机（SVM）两种识别方法进行二维心音图分类和身份识别的可行性，并做了大 量实验分析。根据实验结果数据显示，三种特征都可以实现二维心音图的分类，其中拐点序 列码识别率最高。身份识别中同样是拐点序列码识别率最高，说明拐点序列码更能表征二维 心音图的特征。论文研究成果表明，基于图像处理的二维心音图分类和身份识别具有明显的 可行性和安全性，拥有广阔的应用前景。
单位代码： 10293
密
级：
硕 士 学 位 论 文
论文题目： 基于图像处理的心音图特征提取技术
的研究
学 姓 导 学 研 科 究 专 方
号 名 师 业 向
1010020705 蔡华民 成谢锋 教授 电路与系统 智能信息处理 工学硕士 二零一三年二月
申请学位类别 论文提交日期
Research of Technology on the Phonocardiogram Feature Extraction based on Image Processing
Key words: Heart Sound , PCG , Image Processing , SVM , Euclidean Distance
II
目录
第一章 绪论 ............................................................................................................................................................. 1 1.1 课题研究背景与意义 ................................................................................................................................ 1 1.2 课题研究现状 ............................................................................................................................................ 2 1.2.1 心音图的研究现状 ......................................................................................................................... 2 1.2.2 数字图像处理研究现状 ................................................................................................................. 3 1.3 论文主要内容与创新点 ............................................................................................................................ 3 第二章 心音信号和心音图 ..................................................................................................................................... 6 2.1 心音信号 .................................................................................................................................................... 6 2.1.1 心脏的组成 ..................................................................................................................................... 6 2.1.2 心音的产生机理 ............................................................................................................................. 7 2.1.3 心音心胸传播特性 ......................................................................................................................... 8 2.2 心音研究数据来源 .................................................................................................................................. 10 2.3 二维心音图 ...............................................................................................................................................11 2.3.1 小波降噪和幅值归一化 ................................................................................................................11 2.3.2 二维心音图截取标准 ................................................................................................................... 13 2.4 本章小结 .................................................................................................................................................. 14 第三章 二维心音图预处理 ................................................................................................................................... 15 3.1 线条图像的特点与预处理 ...................................................................................................................... 15 3.1.1 线条图像的特点 ........................................................................................................................... 15 3.1.2 线条图像二值化 ........................................................................................................................... 16 3.1.3 线条图像细化 ............................................................................................................................... 17 3.2 二维心音图的特点与预处理 .................................................................................................................. 18 3.2.1 二维心音图的特点 ....................................................................................................................... 18 3.2.2 二维心音图灰度化 ....................................................................................................................... 18 3.2.3 二维心音图背景归一化 ............................................................................................................... 19 3.2.4 二维心音图二值化 ....................................................................................................................... 23 3.3 二维心音图的细化 .................................................................................................................................. 24 3.3.1 数学形态学细化 ........................................................................................................................... 24 3.3.2 实验结果和分析 ........................................................................................................................... 25 3.4 本章小结 .................................................................................................................................................. 27 第四章 二维心音图特征提取 ............................................................................................................................... 28 4.1 图像特征的定义 ...................................................................................................................................... 28 4.2 全局特征 .................................................................................................................................................. 30 4.2.1 纵横坐标比 ................................................................................................................................... 30 4.2.2 实验结果和分析 ........................................................................................................................... 31 4.3 局部特征 .................................................................................................................................................. 32 4.3.1 拐点序列码 ................................................................................................................................... 32 4.3.2 实验结果和分析 ........................................................................................................................... 34 4.4 二维心音图形变特征 .............................................................................................................................. 35 4.4.1 小波分解系数 ............................................................................................................................... 35 4.4.2 实验结果和分析 ........................................................................................................................... 37 4.5 本章小结 .................................................................................................................................................. 39 第五章 二维心音图识别和应用 ........................................................................................................................... 40 5.1 二维心音图识别方法 .............................................................................................................................. 40
南京邮电大学学位论文原创性声明
本人声明所呈交的学位论文是我个人在导师指导下进行的研究工作及取得 的研究成果。尽我所知，除了文中特别加以标注和致谢的地方外，论文中不包 含其他人已经发表或撰写过的研究成果，也不包含为获得南京邮电大学或其它 教育机构的学位或证书而使用过的材料。与我一同工作的同志对本研究所做的 任何贡献均已在论文中作了明确的说明并表示了谢意。 本人学位论文及涉及相关资料若有不实，愿意承担一切相关的法律责任。
关键词: 心音，心音图，图像处理，支持向量机，欧氏距离
I
Abstract
In mathematics, we can solve abstract problems by drawing it. This indicates that human beings are better at understanding things by eyes. Heart Sound signal is one of the most important human physiological signals. We can convert abstract sound signal into a waveform image that people are more adept at understanding. The two-dimensional phonocardiogram concept of this paper is based on this theory; it is this paper's unique innovation. 2D-PCG can truly record of normal Heart Sounds, extra Heart Sounds, and cardiac murmur. In medicine, 2D-PCG and cardiac auscultation can learn from each other. In the physiological information, 2D-PCG contains rich personal physiological information, such as personal health information and identity information. Image processing technology has matured after years of rapid development. Firstly, using methods of one-dimensional signal processing to realize wavelet noise reduction and amplitude normalized of Heart Sound, and converts it to 2D-PCG with unity and comparability. Then we realize pretreatment of 2D-PCG by image processing, including Gray Processing, Background Normalization, Binarization, and Refinement. Then we analyze of characteristics of 2D-PCG, combining the physiological significance of Heart Sounds and image features of 2D-PCG. What we focused on is the vertical and horizontal coordinate’s ratio and the inflection point sequence code, Of which the vertical and horizontal coordinate’s ratio is proposed based on Heart Sounds' amplitude and time ratio, the inflection point sequence code which can characterize detailed features of the identity information, is raised based on Heart Sounds' bimodal wavelet, trimodal wavelet, quadrumodal wavelet concept. The characteristics of the wavelet decomposition are the low-frequency coefficient matrix of image overall and high-frequency coefficient matrix of image details. At last, we discuss the feasibility of the classification and identification of 2D-PCG by SVM and Euclidean Distance. According to the data from the experimental results, the three features can achieve the classification of 2D-PCG, of which the inflection point sequence code has the highest recognition rate. In identification, the inflection point sequence code also has the highest recognition rate. The results of this study show that the classification and identification of 2D-PCG has some feasibility and safety. 2D-PCG has a broad application prospects.
研究生签名：_____________ 日期：____________
南京邮电大学学位论文使用授权声明
本人授权南京邮电大学可以保留并向国家有关部门或机构送交论文的复印件和电子文 档；允许论文被查阅和借阅；可以将学位论文的全部或部分内容编入有关数据库进行检索； 可以采用影印、缩印或扫描等复制手段保存、汇编本学位论文。本文电子文档的内容和纸质 论文的内容相一致。论文的公布（包括刊登）授权南京邮电大学研究生院办理。 涉密学位论文在解密后适用本授权书。
Thesis Submitted to Nanjing University of Posts and Telecommunications for the Degree of Master of Engineering
By Huamin Cai Supervisor: Prof. Xiefeng Cheng February 2013