學(xué)習(xí)OpenCV

出版時(shí)間:2009-4  出版社:東南大學(xué)出版社  作者:(美)布拉德斯基,(美)克勒 著  頁(yè)數(shù):555  字?jǐn)?shù):605000  
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內(nèi)容概要

《學(xué)習(xí)0penCV》將你置身于迅速發(fā)展的計(jì)算機(jī)視覺(jué)領(lǐng)域。本書(shū)作者是免費(fèi)開(kāi)源0penCV的發(fā)起人,這本書(shū)為你介紹了計(jì)算機(jī)視覺(jué),例證了如何迅速建立使計(jì)算機(jī)能“看”的應(yīng)用程序,以及如何基于計(jì)算機(jī)獲取的數(shù)據(jù)作出決策?! ∮?jì)算機(jī)視覺(jué)幾乎隨處可見(jiàn):安全系統(tǒng)、管理檢驗(yàn)系統(tǒng)、醫(yī)學(xué)圖像分析、無(wú)人機(jī)等。它將Google地圖和Google地球結(jié)合在一起,在LCD屏幕上核對(duì)像素,確保襯衫上的每一個(gè)針腳都完全縫合。OpenCV提供了一個(gè)簡(jiǎn)易實(shí)用的計(jì)算機(jī)視覺(jué)框架以及一個(gè)含有超過(guò)500種可以實(shí)時(shí)運(yùn)行視覺(jué)代碼的函數(shù)的綜合庫(kù)?!秾W(xué)習(xí)OpenCV》在每一章里教授任何OpenCV的開(kāi)發(fā)者或熱愛(ài)者如何在這些實(shí)戰(zhàn)經(jīng)驗(yàn)的幫助下迅速掌握該軟件。這本書(shū)包括了如下內(nèi)容:  對(duì)0penCV全面詳盡的介紹  從照相機(jī)中導(dǎo)入圖片  轉(zhuǎn)換圖像  分割圖像和形狀匹配  模式識(shí)別,包括人臉檢測(cè)      兩到三個(gè)計(jì)量單位間的跟蹤和運(yùn)動(dòng)  立體視覺(jué)中的3D再現(xiàn)  機(jī)器學(xué)習(xí)算法  使機(jī)器能看見(jiàn)是一個(gè)具有挑戰(zhàn)卻又充滿樂(lè)趣的目標(biāo)。無(wú)論你是想建立一個(gè)簡(jiǎn)單的還是復(fù)雜的視覺(jué)應(yīng)用程序,《學(xué)習(xí)OpenCV》都是你入門(mén)的必備教材。

作者簡(jiǎn)介

倫比亞大學(xué)計(jì)算機(jī)科學(xué)教授Gary Rost BradSki博士,斯坦福大學(xué)人工智能實(shí)驗(yàn)室的顧問(wèn)教授,也是Willow Garage公司機(jī)器;人學(xué)研究協(xié)會(huì)的資深科學(xué)家。Ad rian Kaehler博士,Applied Mind S公司的資深科學(xué)家,從事機(jī)器學(xué)習(xí)、統(tǒng)計(jì)建模、計(jì)算機(jī)視覺(jué)和機(jī)器人學(xué)方面的研究。

書(shū)籍目錄

Preface1. Overview  What Is OpenCV?  Who Uses OpenCV?  What Is Computer Vision?  The Origin of OpenCV  Downloading and Installing OpenCV  Getting the Latest OpenCV via CVS  More OpenCV Documentation  OpenCV Structure and Content  Portability  Exercises2. Introduction to OpenCV  Getting Started  First Program--Display a Picture  Second Program--AVI Video  Moving Around  A Simple Transformation  A Not-So-Simple Transformation  Input from a Camera  Writing to an AVI File   Onward  Exercises3. Gettingto KnowOpenCV  OpenCV Primitive Data Types  CvMat Matrix Structure  IplImage Data Structure  Matrix and Image Operators  Drawing Things  Data Persistence  Integrated Performance Primitives  Summary  Exercises4.  HighGUI  A Portable Graphics Toolkit  Creating a Window  Loading an Image  Displaying Images  Working with Video  ConvertImage  Exercises5. Image Processing  Overview  Smoothing  Image Morphology  Flood Fill  Resize  Image Pyramids  Threshold  Exercises6. Image Transforms  Overview  Convolution  Gradients and Sobel Derivatives  Laplace  Canny  Hough Transforms  Remap  Stretch, Shrink, Warp, and Rotate  CartToPolar and PolarToCart  LogPolar  Discrete Fourier Transform (DFT)  Discrete Cosine Transform (DCT)  Integral Images  Distance Transform  Histogram Equalization  Exercises7. Histograms and Matching  Basic Histogram Data Structure  Accessing Histograms  Basic Manipulations with Histograms  Some More Complicated Stuff  Exercises8. Contours  Memory Storage  Sequences  Contour Finding  Another Contour Example  More to Do with Contours  Matching Contours  Exercises9. Image Parts and Segmentation  Parts and Segments  Background Subtraction  Watershed Algorithm  Image Repair by Inpainting  Mean-Shift Segmentation  Delaunay Triangulation, Voronoi Tesselation  Exercises10. Tracking and Motion  The Basics of Tracking  Corner Finding  Subpixel Corners  Invariant Features  Optical Flow  Mean-Shift and Camshift Tracking  Motion Templates  Estimators  The Condensation Algorithm  Exercises11. Camera Models and Calibration  Camera Model  Calibration  Undistortion  Putting Calibration All Together  Rodrigues Transform  Exercises12. Projection and 3D Vision  Projections  Affine and Perspective Transformations  POSIT: 3D Pose Estimation  Stereo Imaging  Structure from Motion  Fitting Lines in Two and Three Dimensions  Exercises13. Machine Learning  What Is Machine Learning  Common Routines in the ML Library  Mahalanobis Distance  K-Means  Naive/Normal Bayes Classifier  Binary Decision Trees  Boosting Random Trees Face Detection or Haar Classifier Other Machine Learning Algorithms Exercises14. OpenCV's Future  Past and Future Directions OpenCV for Artists Afterword BibliographyIndex

章節(jié)摘錄

  Chapter 1 oVerviw  What Is OpenCV?  OpenCV [OpenCV] is an open source (see http://opensource.org) computer vision library available from http://SourceForge.net/projects/opencvlibrary. The library is written in Cand C++ and runs under Linux, Windows and Mac OS X. There is active development on interfaces for Python, Ruby, Matlab, and other languages.  OpenCV was designed for computational efficiency and with a strong focus on realtime applications. OpenCV is written in optimized C and can take advantage of mul ticore processors. If you desire further automatic optimization on Intel architectures [Intel], you can buy Intels Integrated Performance Primitives (IPP) libraries [IPP], which consist of low-level optimized routines in many different algorithmic areas. OpenCV automatically uses the appropriate IPP library at runtime if that library is installed.  One of OpenCVs goals is to provide a simple-to-use computer vision infrastructure that helps people build fairly sophisticated vision applications quickly. The OpenCV library contains over 500 functions that span many areas in vision。 including factory product inspection, medical imaging, security, user interface, camera calibration, stereo vision, and robotics. Because computer vision and machine learning often go hand-inhand, OpenCV also contains a full, general-purpose Machine Learning Library (MLL).This sublibrary is focused on statistical pattern recognition and clustering. The MLL is highly useful for the vision tasks that are at the core of OpenCVs mission, but it is gen eral enough to be used for any machine learning problem.  Who Uses OpenCV?  Most computer scientists and practical programmers are aware of some facet of the role that computer vision plays. But few people are aware of all the ways in which computer vision is used. For example, most people are somewhat aware of its use in surveillance,and many also know that it is increasingly being used for images and yideo on the Web. A few have seen some use of computer vision in game interfaces.

媒體關(guān)注與評(píng)論

  “這本寶庫(kù)對(duì)專(zhuān)業(yè)人員來(lái)講非常有用,對(duì)初涉這個(gè)領(lǐng)域的人們也是個(gè)絕好的工具。像其宣傳的那樣,它是一組計(jì)算機(jī)視覺(jué)算法?!薄  猈illiam T.Freeman.  麻省理工學(xué)院計(jì)算機(jī)科學(xué)與人工智能實(shí)驗(yàn)室“《學(xué)習(xí)0penCV》即將占據(jù)每從從事計(jì)算機(jī)視覺(jué)領(lǐng)域的人的書(shū)架上最顯著的一處?!薄  狣avid Lowe,英屬哥

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用戶評(píng)論 (總計(jì)14條)

 
 

  •   我們看到的, 我們聽(tīng)到的, 和我們摸到的,我們想到的,不一樣。
    所以,要學(xué)習(xí), 要練習(xí), 和體會(huì)。

    如果這個(gè)世界是能夠被自己操縱, 你能從哪些方面入手?

    如果這樣,你理解到的智能是原生存在的還是外部附加的呢?

    到最后, 還有什么區(qū)別呢?

    OpenCV是你倉(cāng)庫(kù)中必備的鋤筢, 學(xué)習(xí)如何鋒利利用, 是操縱自我世界最先的哲學(xué)路徑。

    卡耐基, 不抵用; 富士山, 托不住大地的眼淚; 府南河, 不是故鄉(xiāng)的甜美。

    一切不過(guò)是換了場(chǎng)景, 被處理成自己我可以操縱的“對(duì)象”。

    因此, 強(qiáng)烈推薦看到這本書(shū)的人, 如果你有意看到了這本書(shū)。。。
  •   非常感謝引進(jìn)這本經(jīng)典的原版書(shū),質(zhì)量很好,書(shū)的內(nèi)容非常豐富。把opencv各種數(shù)據(jù)結(jié)構(gòu)和函數(shù)原理,已經(jīng)內(nèi)在聯(lián)系解釋的非常清楚,是初學(xué)opencv非常好的參考書(shū)。建議當(dāng)當(dāng)多進(jìn)影印版的英文原版書(shū)。
  •   這本可以算是OpenCV的必備手冊(cè)了,涵蓋的內(nèi)容很廣很全。

    不過(guò)現(xiàn)在OpenCV 2.0已經(jīng)出來(lái)了,有很多新的東西在此書(shū)中無(wú)法涉及到。
  •   確實(shí)是opencv的經(jīng)典。有中文版的,但是覺(jué)得翻譯的不是很好。還是讀原版的好??!
  •   有些地方想看看中文……
  •   幫老公的弟弟買(mǎi)的,正好需要。比較實(shí)用。
  •   印刷和紙張沒(méi)得說(shuō)咯。建議有英語(yǔ)水平的看,畢竟還是一門(mén)外語(yǔ),理解起來(lái)不如中文直接。
  •   例子詳細(xì),從網(wǎng)上購(gòu)書(shū)到送書(shū)上門(mén)時(shí)間為5天。
  •   該書(shū)是OpenCV方面的入門(mén)基礎(chǔ)讀物,對(duì)于喜歡計(jì)算機(jī)視覺(jué)、圖像處理的人士有一定的參考價(jià)值。另外東南影印書(shū)的印刷質(zhì)量也還可以,清華的中文版就相對(duì)來(lái)講印刷差了很多,而且翻譯的也不怎么樣,建議有一定英文基礎(chǔ)的最好買(mǎi)影印版的看,呵呵。
  •   非常不錯(cuò)的入門(mén)書(shū)籍,廣度和深度恰到好處,適合入門(mén)看。比國(guó)內(nèi)的那本OpenCV書(shū)好太多了。
  •   雖然對(duì)英語(yǔ)要求高,但最起碼不會(huì)誤解原文意思
  •   此書(shū)是當(dāng)時(shí)寫(xiě)論文時(shí)買(mǎi)的,不過(guò)比較一般,opencv相關(guān)知識(shí)在opencv官網(wǎng)上都能找到
  •   書(shū)到得時(shí)候已經(jīng)很陳舊了,有非常明顯的褶皺,估計(jì)就是壓倉(cāng)庫(kù)的,想退貨。年前有事耽誤,現(xiàn)在肯定退不了貨了。
  •   5.25訂的,26發(fā)的貨~我是上海的,到現(xiàn)在還沒(méi)收到,而且在26日就降價(jià)了,訂單不能取消。不知道送貨的要拖到什么時(shí)候
 

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