Learning Image Processing with OpenCV, by Gloria Bueno Garcia, Oscar Deniz Suarez, Jose Luis Espinosa Aranda, Jesus Salido Tercero, Ismael Serrano Gracia
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Learning Image Processing with OpenCV, by Gloria Bueno Garcia, Oscar Deniz Suarez, Jose Luis Espinosa Aranda, Jesus Salido Tercero, Ismael Serrano Gracia
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Exploit the amazing features of OpenCV to create powerful image processing applications through easy-to-follow examples
About This Book
- Learn how to build full-fledged image processing applications using free tools and libraries
- Take advantage of cutting-edge image processing functionalities included in OpenCV v3
- Understand and optimize various features of OpenCV with the help of easy-to-grasp examples
Who This Book Is For
If you are a competent C++ programmer and want to learn the tricks of image processing with OpenCV, then this book is for you. A basic understanding of image processing is required.
What You Will Learn
- Create OpenCV programs with rich user interfaces
- Grasp basic concepts and tasks in image processing such as image types, pixel access techniques, and arithmetic operations with images and histograms
- Explore useful image processing techniques such as filtering, smoothing, sharpening, denoising, morphology, and geometrical transformations
- Get to know handy algorithms such as inpainting and LUTs
- Leverage the color manipulation features of OpenCV to optimize image processing
- Discover how to process a video and the main techniques involved such as stabilization, stitching, and even superresolution
- Understand the new computational photography module that covers high-dynamic range imaging, seamless cloning, decolorization, and non-photorealistic rendering
In Detail
OpenCV, arguably the most widely used computer vision library, includes hundreds of ready-to-use imaging and vision functions and is used in both academia and enterprises.
This book provides an example-based tour of OpenCV's main image processing algorithms. Starting with an exploration of library installation, wherein the library structure and basics of image and video reading/writing are covered, you will dive into image filtering and the color manipulation features of OpenCV with LUTs. You'll then be introduced to techniques such as inpainting and denoising to enhance images as well as the process of HDR imaging. Finally, you'll master GPU-based accelerations. By the end of this book, you will be able to create smart and powerful image processing applications with ease! All the topics are described with short, easy-to-follow examples.
Learning Image Processing with OpenCV, by Gloria Bueno Garcia, Oscar Deniz Suarez, Jose Luis Espinosa Aranda, Jesus Salido Tercero, Ismael Serrano Gracia- Amazon Sales Rank: #829422 in Books
- Published on: 2015-03-27
- Released on: 2015-03-26
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .53" w x 7.50" l, .89 pounds
- Binding: Paperback
- 223 pages
About the Author
Gloria Bueno Garcia
Gloria Bueno Garcia holds a PhD in machine vision from Coventry University, UK. She has experience working as the principal researcher in several research centers, such as UMR 7005 research unit CNRS/ Louis Pasteur Univ. Strasbourg (France), Gilbert Gilkes & Gordon Technology (UK), and CEIT San Sebastian (Spain). She is the author of two patents, one registered type of software, and more than 100 refereed papers. Her interests are in 2D/3D multimodality image processing and artificial intelligence. She leads the VISILAB research group at the University of Castilla-La Mancha. She has coauthored a book on OpenCV programming for mobile devices: OpenCV essentials, Packt Publishing.
Oscar Deniz Suarez
Oscar Deniz Suarez's research interests are mainly focused on computer vision and pattern recognition. He is the author of more than 50 refereed papers in journals and conferences. He received the runner-up award for the best PhD work on computer vision and pattern recognition by AERFAI and the Image File and Reformatting Software Challenge Award by Innocentive Inc. He has been a national finalist for the 2009 Cor Baayen award. His work is used by cutting-edge companies, such as Existor, Gliif, Tapmedia, E-Twenty, and others, and has also been added to OpenCV. Currently, he works as an associate professor at the University of Castilla-La Mancha and contributes to VISILAB. He is a senior member of IEEE and is affiliated with AAAI, SIANI, CEA-IFAC, AEPIA, and AERFAI-IAPR. He serves as an academic editor of the PLoS ONE journal. He has been a visiting researcher at Carnegie Mellon University, Imperial College London, and Leica Biosystems. He has coauthored two books on OpenCV previously.
Jose Luis Espinosa Aranda
Jose Luis Espinosa Aranda holds a PhD in computer science from the University of Castilla-La Mancha. He has been a finalist for Certamen Universitario Arquimedes de Introduccion a la Investigacion cientifica in 2009 for his final degree project in Spain. His research interests involve computer vision, heuristic algorithms, and operational research. He is currently working at the VISILAB group as an assistant researcher and developer in computer vision topics.
Jesus Salido Tercero
Jesus Salido Tercero gained his electrical engineering degree and PhD (1996) from Universidad Politecnica de Madrid (Spain). He then spent 2 years (1997 and 1998) as a visiting scholar at the Robotics Institute (Carnegie Mellon University, Pittsburgh, USA), working on cooperative multirobot systems. Since his return to the Spanish University of Castilla-La Mancha, he spends his time teaching courses on robotics and industrial informatics, along with research on vision and intelligent systems. Over the last 3 years, his efforts have been directed to develop vision applications on mobile devices. He has coauthored a book on OpenCV programming for mobile devices.
Ismael Serrano Gracia
Ismael Serrano Gracia received his degree in computer science in 2012 from the University of Castilla-La Mancha. He got the highest marks for his final degree project on person detection. This application uses depth cameras with OpenCV libraries. Currently, he is a PhD candidate at the same university, holding a research grant from the Spanish Ministry of Science and Research. He is also working at the VISILAB group as an assistant researcher and developer on different computer vision topics.
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Most helpful customer reviews
7 of 7 people found the following review helpful. Interesting examples By Christian S. The first chapter was challenging. The setup and documentation is targeted to Windows users.There are some hints on how to do it on Linux but not really on a Mac. Luckily Internet helps on that.This is what you need to do on a Mac if you have Homebrew installed:brew install qtbrew install ffmpegbrew install opencv --with-ffmpeg --with-qt --devel(--devel to install version 3.0.0-rc1)After I got OpenCV working I could ran the examples from the first chapter.There are some minor tweaks you need to do in the examples to make them work on Mac.I also found a minor typo in the example of reading and writing images:imshow(argv[2], out_image); // it was “in_image”The source code provided includes the “pro” configuration files for the Qt Creator IDE.I didn't need to use any IDE though, I just compiled and run on the terminal like this:g++ `pkg-config --libs-only-other opencv` `pkg-config --libs QtGui` -std=c++11 -stdlib=libstdc++ -o example example.cppChapter 2 explains the fundamental data types and basic data operations that OpenCV offers.It also introduces briefly histograms. The histogram tutorial on the OpenCV website is more detailed though.Chapter 3 deals with the basic image processing techniques (filtering, morphological and geometrical transformations, etc.) and chapter 4 takes care of color processing.The last 3 chapters are the most interesting. They do cover more practical and challenging applications of image processing. Chapter 5 has video stabilization, superresolution and my favorite example of the book, stitching overlapped images to build panoramas. That was very neat. Chapter 6 has a really cool HDR example and other photography topics. Chapter 7 finishes with GPU performance optimizations. You really need OpenCV 3.0.0 for those examples.In summary I would recommend the book, in particular for the last 3 chapters. Those really show what OpenCV can do and how complex the code could be.My only complains are code formatting issues like indentation and a minor typo in the code that you have to fix to get the expected results (in my Mac at least). Also I have to mention that the source code doesn’t include all the chapters (at least at the moment I downloaded the zip file). You will need to copy it from the book for chapters 1, 4 and 6.I hope chapters 5 and 6 could be expanded more in a future edition targeted for advanced OpenCV users.
3 of 3 people found the following review helpful. Wanna get comfy with OpenCV? This book shows you how! By adnan baloch This book is intended for C++ programmers willing to enter the exciting world of image processing. However those hoping for facial recognition and tracking examples need to look elsewhere. The proliferation of web cameras and shift towards digital photography and video production has led to a vast increase in applications that target the PC's ability to manipulate photos and videos. The examples in this book are easy to understand, providing the reader with a solid foundation to explore the features of the OpenCV V3 library and develop groundbreaking new applications limited only by the infinite boundaries of the human imagination. Programmers on a budget will really appreciate this book because all the examples can be compiled on Linux using just free software. The book begins with installation of OpenCV and configuring it with CMake on Windows/Linux. For those so inclined, Microsoft compilers can also be used. Readers are introduced to the power of OpenCV with basic but terse code snippets like reading and writing image and video files. Using QtCreator, the book shows how to make the most of the UI possibilities of the Qt framework when used in conjunction with OpenCV. Inquisitive readers will be delighted by simple examples showing how complex operations like denoising and restoring damaged images are made easy with OpenCV. An entire chapter is devoted to color space based segmentation and color transfer methods, driving home the importance of using the correct color space as well as image processing using different color models. The next chapter shows complete working examples written in C++ that implement interesting and useful techniques like video stabilization, super-resolution from several low quality images of the same scene and stitching to create panoramas. Creating high dynamic range images and non realistic images is tackled in the chapter dealing with computational photography. Image processing is a highly intensive operation that can really test the patience of professionals working under a tight deadline. The chapter on accelerating such functions with multiple CPU cores or a dedicated GPU addresses this important concern and shows how to easily achieve a speedup of upto sixfold by harnessing the latent parallel processing power of commodity hardware made possible with the OpenCL library. In a nutshell, computer science students interested in practical application of their knowledge as well as C++ programmers looking to expand their development horizons will appreciate this book's excellent coverage of image and video processing magic. In fact, it is not inconceivable to expect an individual armed with just this book and "C++ for dummies" to develop their own Photoshop clone.
2 of 2 people found the following review helpful. Image Processing + C++ = OpenCV By Oleg Okun This book is for somebody who (1) knows C++ OR 2) knows basic image processing operations) AND 3) wants to use OpenCV - one of the standard tools to do image processing in C++. There is a lot of C++ code illustrating the implementations (in OpenCV) of the basic image processing operations such as image filtering. morphological operators, geometrical transformations, handling different color spaces, resolution enhancement and stitching in video, computational photography as well as GPU based image processing acceleration. Therefore I think this book would be useful for students and early stage researchers who would like to quickly get an introduction into the basics of OpenCV. The code examples in the book could also be used by university teachers in programming exercises accompanying image processing/computer vision courses. In addition, detailed installation instructions provide helpful guidelines for beginners.
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