计算机视觉架构：从算法到Verilog芯片实现

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"《计算机视觉架构：从算法到Verilog芯片设计》由洪钟撰写，主要探讨了计算机视觉领域的体系结构，以及如何使用Verilog语言进行芯片设计。这本书首次出版于2014年，由John Wiley & Sons Singapore Pte. Ltd.发行，版权受法律保护。" 计算机视觉是信息技术中的一个关键领域，它涉及到图像处理、机器学习和人工智能等多个交叉学科。本书《Architectures for Computer Vision》深入讲解了计算机视觉系统的构建，从算法层面到硬件实现的全过程。作者洪钟来自韩国浦项科技大学，他将理论知识与实践应用相结合，为读者提供了全面的视角。首先，书中的"算法"部分可能涵盖了图像预处理、特征检测、目标识别和追踪等基础和高级的计算机视觉技术。这些算法是计算机视觉系统的核心，它们处理输入的图像数据，提取有用信息，并进行决策或预测。例如，可能会讨论SIFT（尺度不变特征转换）、HOG（方向梯度直方图）或卷积神经网络（CNN）等流行的算法。其次，"计算机体系结构"部分可能涉及计算机硬件如何支持并优化这些视觉算法的执行。这可能包括处理器设计、内存层次结构、并行计算以及针对特定任务定制的硬件加速器。作者可能探讨了如何通过优化硬件架构来提高计算机视觉处理的效率和性能。然后，"芯片设计"部分重点讲述了使用Verilog语言来实现计算机视觉算法的硬件化。Verilog是一种硬件描述语言，广泛用于数字电路的设计和验证。通过Verilog，工程师可以描述算法的逻辑行为，并将其转化为可编程逻辑器件（如FPGA）或ASIC（专用集成电路）的设计。这部分可能会包含Verilog的基本语法、模块化设计方法以及如何将高级算法映射到硬件实例。最后，书中可能还涉及了实际应用案例，如自动驾驶、监控系统、医疗影像分析等，这些都依赖于高效的计算机视觉技术。此外，可能还包括了设计流程、仿真验证和测试方法，帮助读者将理论知识转化为实际项目。《Architectures for Computer Vision》旨在连接计算机视觉的理论研究与实际的硬件实现，通过Verilog这一桥梁，为读者展示了从概念到芯片的完整过程。这本书不仅对计算机视觉研究人员，也对电子工程和嵌入式系统开发者具有很高的参考价值。

xiv Preface

and references. The purpose of the rst part is to introduce the vision implementation methodology, the

Verilog HDL for image processing, and the Verilog HDL simulator for designing the vision architecture.

Chapter 1 deals with the taxonomy of the general and specialized algorithms and architectures that are

considered typical in vision technology. The pros and cons of the different implementations are discussed,

and the dedicated implementation by Verilog HDL design addressed. Chapter 2 introduces the basics of

Verilog HDL and coding examples for communication and control modules. These modules are general

building blocks for designing vision architectures. Chapter 3 introduces Verilog circuit modules, such as

processor, memory, and pipelined array, which are the building blocks of the vision architectures. The

vision architectures are designed using processors, memories, and possibly pipelined arrays, connected

by the communication and control modules. Chapter 4 introduces the Verilog vision simulators, specially

built for designing vision architectures. The simulator consists of the unsynthesizable module, which

functions as an interface for image input and output, and the synthesizable module, which is a platform

for building serial and parallel architectures. This platform is tailored to the specic architectures in later

chapters.

The second part, comprising Chapters 5–7, introduces the fundamentals of intermediate vision algo-

rithms. Instead of treating diverse elds in vision research, this part focuses on the energy minimization,

stereo, motion, and fusion of vision modules. Chapter 5 introduces the energy function, which is a

common concept in computer vision algorithms. The energy function is explained in terms of Markov

random eld (MRF) estimation and the free energy concept. The energy minimization methods and the

structure of a typical energy function are also explained. Chapter 6 is dedicated to stereo vision. Instead

of surveying the extensive research done, this chapter focuses on the constraints and energy minimiza-

tion. A typical energy function that is subsequently designed with various architectures is discussed.

Chapter 7 deals with motion estimation and fusion of vision modules. Instead of an extensive survey, this

chapter focuses on the motion principles and the continuity concept that unify the various constraints in

motion estimation. This chapter also deals with the fusion of vision modules, directly with intermediate

variables, bypassing the 3D variables, which give strong constraints for determining the intermediate

vision variables. This chapter closes with a set of equations linking the 2D variables directly, i.e. blur

diameter, surface normal, disparity, and optical ow.

The third part, which comprises Chapters 8–10, introduces the algorithms and architectures of the

major algorithms: relaxation, dynamic programming (DP), belief propagation (BP), and graph cuts (GC).

The computational structures and possible implementations are also discussed. Chapter 8 introduces the

concept underlying the relaxation algorithm and architecture. In addition to the Gauss–Seidel and Jacobi

algorithms, this chapter introduces other types of architectures: specically, extensions to the Gauss–

Seidel–Jacobi architecture. In Chapter 9, the concept underlying the DP algorithm and architecture is

introduced, and the computational structures of various DP algorithms discussed. Finally, the algorithms

and architectures of BP and GC are addressed in Chapter 10, and their computational structures and

possible implementations discussed.

The fourth part, which comprises Chapters 11–14, is dedicated to the Verilog design of stereo matching

with the major architectures: relaxation, DP, and BP. All the designs are provided with complete Verilog

HDL codes that have been veried by function simulation and synthesis. Chapter 11 addresses the Verilog

design of the relaxation architecture. Chapter 12 deals with the Verilog design of serial architectures for

the DP. The design is aimed at executing stereo matching with the serial vision simulator. Chapter 13 intro-

duces the systolic array in Verilog HDL. This chapter explains in detail how to design the control module

and the systolic array, connected by local neighborhood connections. Finally, Chapter 14 deals with BP

design for stereo matching. This chapter also explains in detail the design methods with Verilog HDL.

All the designs are accompanied by complete source codes that have all been proven correct via

simulation and synthesis tests. A package of the codes in the textbook, and the complementary codes, is

provided separately for readers. The codes are carefully provided with the general constructs in standard

Verilog HDL, which is free from IPs and vendor-dependent codes. I hope that this book will provide

an important opportunity that stirs the reader’s ability to develop more advanced vision architectures

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