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《经典原版书库·计算机与机器视觉:理论、算法与实践(英文版·第4版)》清晰而系统地阐述了计算机与机器视觉的基本概念,对重要的图像处理和计算机视觉 算法进行了详细分析,既介绍理论的基本元素,又强调算法和实际设计约束,并通过实际案例演示具体技术的应用。前三版已经奠定了《经典原版书库·计算机与机 器视觉:理论、算法与实践(英文版·第4版)》在机器视觉领域中****的地位,这一版进行了全面更新和修订,增加了*新进展,是一部全面而且与时俱进的 权威著作。

Foreword
Preface
About the Author,
Acknowledgements
Glossary of Acronyms and Abbreviations
CHAPTER l Vision, the Challenge
1.1 Introduction-Man and His Senses
1.2.1 The Process of Recognition
1.2.2 Tackling the Recognition Problem
1.2.4 Scene Analysis
1.2.5 Vision as Inverse Graphics
1.3 From Automated Visuallnspection to Surveillance
1.4 What This Book is About
1.5 The Following Chapters
1.6 Bibliographical Notes

PART l LOW-LEVEL VISION
CHAPTER 2 Images and Imaging Operations
2.1 Introduction
2.1.1 Gray Scale Versus Color
2.2 Image Processing Operations
2.2.1 Some Basic Operations on Grayscale Images
2.2.2 Basic Operations on Binary Images
2.3 Convolutions and Point Spread Functions
2.4 Sequential Versus Parallel Operations
2.6 Bibliographical and Historical Notes
CHAPTER 3 Basic Image Filtering Operations
3.1 Introduction
3.2 Noise Suppression by Gaussian Smoothin;
3.4 Mode Filters
3.5 Rank Order Filters
3.6 Reducing Computational Load
3.7 Sharp-UnsharpMasking
3.8 Shifts Introduced by Median Filters
3.8.1 Continuum Model of Median Shifts
3.8.2 Generalization to Grayscale Images
3.8.3 Problems with Statistics
3.9 Discrete Model of Median Shifts
3.10 Shifts Introduced by Mode Filters
3.11 Shifts Introduced by Mean and Gaussian Filters
3.12 Shifts Introduced by Rank Order Filters
3.12.1 Shifts in Rectangular Neighborhoods
3.13 The Role of Filters in Industrial Applications of Vision
3.14 Colorin Image Filtering
3.16 Bibliographical and Historical Notes
3.16.1 More Recent Developments
CHAPTER 4 Thresholding Techniques .,
4.2 Region-GrowingMethods
4.3.1 Finding a Suitable Threshold
4.3.2 Tackling the Problem of Bias in Threshold Selection
4.3.3 Summary
4.4 Adaptive Thresholding
4.4.1 The Chow and Kaneko Approach
4.4.2 Local Thresholding Methods
4.5 More Thoroughgoing Approaches to Threshold Selection
4.5.1 Variance-Based Thresholding
4.5.2 Entropy-Based Thresholding
4.6 The Global Valley Approach to Thresholding
4.7 Practical Results Obtained Using the Global Valley
4.8 Histogram Concavity Analysis
4.10.1 More Recent Developments
CHAPTER 5 Edge Detection
5.1 Introduction
5.2 Basic Theory of Edge Detection
……

PART 2 INTERMEDIATE-LEVEL VISION
PART 3 3-D VISION AND MOTIONPART
PART 4 TOWARD REAL-TIME PATTERN RECOGNITION SYSTEMS

《经典原版书库·计算机与机器视觉:理论、算法与实践(英文版·第4版)》通过丰富的实例和案例研究揭示开发实际视觉系统的来龙去脉,展示了如何在实践中 应用这些基本原理。新增章节包含监视和驾驶辅助系统方面的案例研究,给出了计算机视觉中那些**领域应用的实际方法。对于必要的数学工具和关键理论都进行 了详细解释和很好的实例说明。内容更丰富,覆盖人类虹膜定位、图像拼接、使用RANSAC进行线条检测、性能度量和高光谱成像等主题。每章的“More Recent Developments”介绍了相关主题的一些新进展。

E.R.Davies,**机器视觉专家、英国物理学会会士、英国机器视觉协会的执行委员,现为伦敦大学**霍洛威学院机器视觉荣誉退休教授。 Davies教授在图像分析、自动视觉检测和噪声**技术等方面有丰富的教学和科研经验。他已发表200余篇论文,出版3部著作。他曾被英国机器视觉协会 授予杰出会士奖,并且还是国际模式识别协会的会士。