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.
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“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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