具体描述
《图像仿射不变方法研究》研究的重点是旋转不变纹理分类和尺度不变模式识别。对旋转不变纹理分类的研究，我们提出了两种新方法，即基于Gabor小波的旋转不变纹理分类方法和基于圆形Gabor小波的旋转不变纹理分类方法。同时为了测定旋转纹理的角度，我们又提出了一种基于相位一致性的方向估计算法。对尺度不变模式识别的研究，我们提出了基于经验模态分解和梅林径向调和分解的方法。
《图像仿射不变方法研究》可作为模式识别、图像处理及相近专业的研究生和专业人员的教材或参考书。
作者简介
目录信息
目录
Chapter ⅠIntroduction
1.1 Background
1.2 The Problem of Invariance
1.3 Scope of the Research and Contribution of this Book
1.4 The Mathematical Background
1.5 Organization of This Book
1.6 Summary
Chapter ⅡReview of the Previous Works
2.1 Review of Rotation Invariant Texture Classification
2.2 Review of the Correlation Filters about Scale Invariant Pattern Recognition
2.3 Summary
Chapter ⅢThe Proposed Invariant Methods
3.1 Proposed Rotation Invariant Texture Classification Methods[170,171,173,174]
3.2 Proposed Orientation Estimation Method[172]
3.3 Proposed Scale Invariant Pattern Recognition Method[168,169]
3.4 Summary
Chapter ⅣExperimental Results and Analysis
4.1 Experiments for Rotation Invariant Texture Classification
4.2 Experiments for Orientation Estimation
4.3 Experiments for Scale Invariant Pattern Recognition
4.4 Summary
Chapter ⅤConclusion
5.1 Rotation-invariant texture classification Using Gabor wavelet
5.2 Rotation-Invariant Texture Classification Using Circular Gabor Wavelets
5.3 Orientation estimat on from phase congruency
5.4 Scale Invariant Pattern Recofnition
Reference
· · · · · · (收起)
Chapter ⅠIntroduction
1.1 Background
1.2 The Problem of Invariance
1.3 Scope of the Research and Contribution of this Book
1.4 The Mathematical Background
1.5 Organization of This Book
1.6 Summary
Chapter ⅡReview of the Previous Works
2.1 Review of Rotation Invariant Texture Classification
2.2 Review of the Correlation Filters about Scale Invariant Pattern Recognition
2.3 Summary
Chapter ⅢThe Proposed Invariant Methods
3.1 Proposed Rotation Invariant Texture Classification Methods[170,171,173,174]
3.2 Proposed Orientation Estimation Method[172]
3.3 Proposed Scale Invariant Pattern Recognition Method[168,169]
3.4 Summary
Chapter ⅣExperimental Results and Analysis
4.1 Experiments for Rotation Invariant Texture Classification
4.2 Experiments for Orientation Estimation
4.3 Experiments for Scale Invariant Pattern Recognition
4.4 Summary
Chapter ⅤConclusion
5.1 Rotation-invariant texture classification Using Gabor wavelet
5.2 Rotation-Invariant Texture Classification Using Circular Gabor Wavelets
5.3 Orientation estimat on from phase congruency
5.4 Scale Invariant Pattern Recofnition
Reference
· · · · · · (收起)
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