基于Contourlet变换和局部二值模式图像纹理分类研究及其应用

摘要.................................................................................................................................I Abstract...........................................................................................................................III 目录................................................................................................................................V Contents.........................................................................................................................VII 第一章绪论 (1)

1.1课题研究背景和意义 (1)

1.2图像纹理特征分类的概述 (2)

1.2.1纹理的概念 (2)

1.2.2纹理特征提取的研究现状 (3)

1.3局部二值模式的研究现状 (6)

1.4Contourlet变换的纹理分类研究现状 (7)

1.5本文的结构安排 (7)

第二章纹理分类的相关工作 (9)

2.1引言 (9)

2.2局部二值模式（LBP） (9)

2.3LBP的相关变种 (11)

2.3.1显性局部二值模式（DLBP） (12)

2.3.2完备局部二值模式（CLBP） (13)

2.3.3分类连贯局部二值模式（SCLBP） (15)

2.4局部二值模式的典型应用 (17)

2.4.1纹理分类 (17)

2.4.2人脸识别 (17)

2.4.3图像检索 (19)

2.5本章小结 (19)

第三章基于BRINT的尺度不变纹理分类 (20)

3.1引言 (20)

3.2二值旋转不变与抗噪 (21)

3.2.1BRINT_S描述子 (21)

3.2.2BRINT_M描述子 (22)

3.2.3BRINT_C描述子 (23)

3.3尺度选择的BRINT特征提取 (23)

3.3.1特征抽取方法 (23)

3.3.2特征匹配方法 (26)

3.4实验结果与分析 (27)

3.5本章小结 (30)

第四章基于Contourlet变换的纸币纹理分类 (31)

4.1引言 (31)

4.2Contourlet变换的原理 (32)

4.2.1金字塔框架 (32)

4.2.2迭代方向滤波器组(DFB) (33)

4.2.3多尺度、多方向分解 (34)

4.3基于Contourlet变换的纸币纹理特征提取与识别 (36)

4.3.1特征向量构成 (37)

4.3.2支持向量机分类器 (39)

4.3.3最近邻分类器 (40)

4.4实验结果与分析 (41)

4.4.1与常用的特征提取算法进行比较 (41)

4.4.2轮廓波分解层数与识别率的关系 (42)

4.4.3讨论结果 (43)

4.5本章小结 (43)

结论与展望 (44)

参考文献 (46)

攻读硕士学位期间发表论文 (51)

学位论文独创性声明 (52)

学位论文版权使用授权声明 (52)

致谢 (53)

Contents

Abstract(In Chinese)........................................................................................................I Abstract(In English)......................................................................................................III Contents(In Chinese)......................................................................................................V Contents(In English)....................................................................................................VII Chapert1Introduction (1)

1.1Background and signficance (1)

1.2An overview of Image texture feature classification (2)

1.2.1The concept of texture (2)

1.2.2The current research status of texture feature extraction (3)

1.3The research status of local binary pattern (6)

1.4The research status of Contourlet transform (7)

1.5Main content arrangement of this disseration (7)

Chaper2The related work of Texture classification (9)

2.1Introduction (9)

2.2Local Binary Pattern（LBP） (9)

2.3The related variants of LBP (11)

2.3.1Dominent local binary pattern（DLBP） (12)

2.3.2Completed local binary pattern（CLBP） (13)

2.3.3Sorted consecutive local binary pattern（SCLBP） (15)

2.4Typical applications of LBP (17)

2.4.1Texture classification (17)

2.4.2Face recognition (17)

2.4.3Image retrieval (19)

2.5Summary (19)

Chaper3Scale invariant texture classification Based on BRINT (20)

3.1Introduction (20)

3.2Binary rotation invariant and Resistance to noise (21)

3.2.1BRINT_S descriptor (21)

3.2.2BRINT_M descriptor (22)

3.2.3BRINT_C descriptor (23)

3.3Scale selective BRINT feature extraction (23)

3.3.1Feature extraction methods (23)

3.3.2Feature matching method (26)

3.4Experimental Results and Analysis (27)

3.5Summary (30)

Chaper4Note texture classification Based on Contourlet Transform (31)

4.1Introduction (31)

4.2The principle of Contourlet Transform (32)

4.2.1Pyramid framework (32)

4.2.2Iteration direction filter Banks(DFB) (33)

4.2.3Multi-scale decomposition and multiple directions (34)

4.3Note texture feature extraction and recognition Based on

Contourlet Transform (36)

4.3.1Feature vector composition (37)

4.3.2Support vector machine classifier (39)

4.3.3Nearest neighbor classifier (40)

4.4Experimental Results and Analysis (41)

4.4.1Comparing with common feature extraction algorithm (41)

4.4.2The relation of Contour wavelet decomposition layers and recognition

rate (42)

4.4.3Discuss the results (43)

4.5Summary (43)

Conclusion and Prospect (44)

Reference (46)

Published Papers During the Degree Period (51)

Academic Dissertatio Originality Declaration (52)

Contents

Academic Dissertatio Copyright Use Authorization Declaration (52)

Acknowledgements (53)