機(jī)器視覺(jué)

前言

An important focus of advances in mechatronics and robotics is the addition of sensory inputs to systems with increasing "intelligence." Without doubt, sight is the "sense of choice." In everyday life, whether driving a car or threading a needle , we depend first on sight. The addition of visual perception to machines promises the greatest improvement and at the same time presents the greatest challenge.Until relatively recently, the volume of data in the images that make up a video stream has been a serious deterrent to progress. A single frame of very modest resolution might occupy a quarter of a megabyte, so the task of handling thirty or more such frames per second requires substantial computer resources.Fortunately, the computer and communications industries' investment in entertainment has helped address this challenge. The transmission and processing of video signals are an easy justification for selling the consumer increased computing speed and bandwidth. A digital camera, capable of video capture, has already become a fashion accessory as part of a mobile phone. As a result, video signals have become more accessible to the serious engineer. But the task of acquiring a visual image is just the tip of the iceberg.While generating sounds and pictures is a well-defined process （speech generation is a standard "accessibility" feature of Windows）, the inverse task of recognizing connected speech is still at an unfinished state, a quarter of a century later, as any user of "dictation" software will attest. Still, analyzing sound is not even in the same league with analyzing images, particularly when they are of realworld situations rather than staged pieces with synthetic backgrounds and artificial lighting.The task is essentially one of data reduction. From the many megabytes of the image stream, the required output might be a simple "All wheel nuts are in place" or "This tomato is ripe." But images tend to be noisy, objects that look sharp to the eye can have broken edges, boundaries can be fuzzy, and straight lines can be illusory. The task of image analysis demands a wealth of background know-how and mathematical analytic tools.Roy Davies has been developing that rich background for well over two decades. At the time of the UK Robotics Initiative, in the 1980s, Roy had formed a relationship with the company United Biscuits. We fellow researchers might well have been amused by the task of ensuring that the blob of jam on a "Jaffacake" had been placed centrally beneath the enrobing chocolate.

內(nèi)容概要

本書(shū)是機(jī)器視覺(jué)課程的理想教材，作者清晰、系統(tǒng)地闡述了機(jī)器視覺(jué)的基本概念，介紹理論的基本元素的同時(shí)強(qiáng)調(diào)算法和實(shí)用設(shè)計(jì)的約束。書(shū)中闡述各個(gè)主題時(shí)，既闡述了基本算法，又介紹了數(shù)學(xué)工具。此外，本書(shū)還使用案例演示具體技術(shù)的應(yīng)用，并闡明設(shè)計(jì)現(xiàn)實(shí)機(jī)器視覺(jué)系統(tǒng)的關(guān)鍵約束。    本書(shū)適合作為高等院校計(jì)算機(jī)及電子工程相關(guān)專(zhuān)業(yè)研究生的教材，更是從事機(jī)器視覺(jué)、計(jì)算機(jī)視覺(jué)和機(jī)器人領(lǐng)域研究的人員不可多得的技術(shù)參考書(shū)。

作者簡(jiǎn)介

E.R.Davies，著名機(jī)器視覺(jué)專(zhuān)家。英國(guó)物理學(xué)會(huì)會(huì)士、IEE會(huì)士、英國(guó)機(jī)器視覺(jué)協(xié)會(huì)的執(zhí)行委員。畢業(yè)于牛津大學(xué)，現(xiàn)任倫敦大學(xué)皇家霍洛威學(xué)院機(jī)器視覺(jué)教授。在機(jī)器視覺(jué)、圖像分析、自動(dòng)視覺(jué)檢測(cè)、噪聲抑制技術(shù)等方面有豐富的教學(xué)和科研經(jīng)驗(yàn)。

書(shū)籍目錄

CHAPTER 1　Vision, the ChallengePART 1　LOW-LEVELVISION　  CHAPTER 2　Images and Imaging Operations  CHAPTER 3　Basic Image Filtering Operations  CHAPTER 4　Thresholding Techniques  CHAPTER 5　Edge Detection  CHAPTER 6　Binary Shape Analysis  CHAPTER 7　Boundary Pattern Analysis  CHAPTER 8　Mathematical MorphologyPART 2　INTERMEDIATE-LEVELVISION　  CHAPTER 9　Line Detection  CHAPTER 10　Circle Detection  CHAPTER 11　The Hough Transform and Its Nature  CHAPTER 12　Ellipse Detection  CHAPTER 13　Hole Detection  CHAPTER 14　Polygon and Corner Detection  CHAPTER 15　Abstract Pattern Matching TechniquesPART 3　3-DVISION AND MOTION　443  CHAPTER 16　The Three-dimensional World  CHAPTER 17　Tackling the Perspective n-Point Problem  CHAPTER 18　Motion  CHAPTER 19　Invariants and Their Applications  CHAPTER 20　Egomotion and Related Tasks  CHAPTER 21　Image Transformations and Camera CalibrationPART 4　TOWARD REAL-TIME PATTERN RECOGNITIONS YSTEMS　  CHAPTER 22　Automated Visual Inspection  CHAPTER 23　Inspection of Cereal Grains  CHAPTER 24　Statistical Pattern Recognition  CHAPTER 25　Biologically Inspired Recognition Schemes  CHAPTER 26　Texture  CHAPTER 27　Image Acquisition  CHAPTER 28　Real-time Hardware and Systems Design ConsiderationsPART 5　PERSPECTIVES ON VISION　  CHAPTER 29　Machine Vision: Art or Science?APPENDIX　Robust StatisticsList of Acronyms and Abbreviations　References　Author Index　Subject Index　

章節(jié)摘錄

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媒體關(guān)注與評(píng)論

“本書(shū)將圖像處理的理論與應(yīng)用實(shí)踐完美地結(jié)合起來(lái)，是機(jī)器視覺(jué)領(lǐng)域研究人員的必讀之作?！薄　　狫ohn Billingsley，南昆士蘭大學(xué)“前兩版已經(jīng)奠定了本書(shū)在機(jī)器視覺(jué)領(lǐng)域中獨(dú)一無(wú)二的地位，它是對(duì)重要的圖像處理和計(jì)算機(jī)視覺(jué)算法進(jìn)行詳細(xì)分析的知識(shí)寶庫(kù)！這一版在此基礎(chǔ)之上增加了最新進(jìn)展，是一部全面而且與時(shí)俱進(jìn)的權(quán)威著作。”　　——Farzin Deravi，肯特大學(xué)

編輯推薦

《機(jī)器視覺(jué)理論、算法與實(shí)踐(英文版·第3版)》能夠滿足廣大讀者學(xué)習(xí)和掌握機(jī)器視覺(jué)知識(shí)的需求。全書(shū)圖文并茂，清晰、系統(tǒng)地闡述了基本概念，提供了豐富的應(yīng)用案例和代碼，強(qiáng)調(diào)了算法和實(shí)用設(shè)計(jì)的各種約束條件。新版做了全面的更新，反映了最新進(jìn)展，內(nèi)容更加全面。40年來(lái)，機(jī)器視覺(jué)在各行各業(yè)得到了廣泛的應(yīng)用，包括自動(dòng)檢測(cè)、機(jī)器人組裝、行車(chē)導(dǎo)引、流量監(jiān)控、簽名驗(yàn)證、生物測(cè)量、遙感圖像分析等。但是另一方面，面對(duì)大量新的研究成果，要充分理解相關(guān)的理論和應(yīng)用，進(jìn)行算法和系統(tǒng)的設(shè)計(jì)，卻越來(lái)越困難?！稒C(jī)器視覺(jué)理論、算法與實(shí)踐(英文版·第3版)》是機(jī)器視覺(jué)課程的理想教材，已經(jīng)成為國(guó)內(nèi)外很多名校的指定教學(xué)參考書(shū)。同時(shí)，《機(jī)器視覺(jué)理論、算法與實(shí)踐(英文版·第3版)》也是工程技術(shù)人員不可或缺的權(quán)威參考書(shū)。

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