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OpenCV Essentials
This book is intended for C++ developers who want to learn how to implement the main techniques of OpenCV and get started with it quickly. Working experience with computer vision / image processing is expected.
214 pages, Kindle Edition
First published January 1, 2014
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Displaying 1 - 9 of 9 reviews
February 23, 2021
Sebagian skimming, sebagian rada lama dipahami :D. Sayang buku ini pake versi C++, mungkin klo di kasus skimming, algoritma di Python akan lebih mudah dipahami. Untuk versi penjelasan yang paling lengkapnya sendiri docs.opencv.org tetap juaranya.
September 29, 2014
A few weeks ago I have been selected by Packt Publishing to review the new book “OpenCV Essentials” by Oscar Deniz Suarez et.al. Thus here is my objective review:
This book is for people who have at least basic knowledge in OpenCV and Computer Vision, if you are new in OpenCV maybe this book won’t be the suitable one. Additionally all the examples are in C++ for Visual Studio, I did not like the last restriction, but it was necessary for some examples. This book show some upcoming OpenCV functions for the next release 3.0 (available at this time in Alpha version), and there are a lot of very useful functions.
Let’s begin with the main review. First chapters are about OpenCV basic functionalities (load images, brightness, contrast, color spaces, arithmetic and geometrical transforms). For every topic they show the code, explanation and results. The book shows tips in each topic, giving you the opportunity to investigate more about the functionality, and also they usually share links to Scientific Papers, thus, if you have a better idea to improve that function it helps you to do research about it.
I found Threshold topic in Chapter 4 (What’s in the Image? Segmentation) very useful and didactic, a lot of developers (also experts) made mistakes in this topic when choosing the type of threshold. Until here, Chapters were about main OpenCV functions, but here on-wards the book becomes better and very useful with content about Pattern Recognition, Classification, also Video Processing. Thus, I will discuss separated every chapter.
Chapter 5: Focusing on the Interesting 2D Features: This Chapter is totally based in Keypoints and its variations, the book provide a lot of examples and also the matching between images using Keypoints. Additionally some new OpenCV feature detectors of the new release are explained (KAZE and AKAZE).
Chapter 6: Where’s Wally? Object Detection: The main topics are Cascade detectors and Latent SVM. The book shows an example of basic pedestrian detection in a few lines of code using HOG cascade detector. Also, if you need to train your own cascade, you will find a detailed explanation about how to do it.
Chapter 7: What is he Doing? Motion: Due to I developed this kind of systems, I particularly liked this Chapter. Topics like Video tracking, Motion and Background subtraction are now included in the new OpenCV 3.0 and certainly will be very useful for everyone who is developing/researching this area. The book does not show the typical Optical Flow, but explains and optimized and faster Lucas-Kanade optical flow instead.
Chapter 8: Advanced Topics: If you are interested in Machine learning, Classification, or CUDA GPU programming this Chapter will be very useful too. It shows how to use the Random Forest classifier, one of the best classifiers available in recognition power and efficiency. Also the typical SVM is explained with a simple version of a recognition system.
To summarize, if you are using OpenCV for basic image processing certainly you will be more interested in Chapter 1 to 4, and maybe 5. If you need more depth knowledge and want to do complex Pattern Recognition systems you will be interested in Chapter 5 on-wards. The main weak point of this book is about pre-processing image explanation, although authors show some of them, they do not explain the real potential of the pre-processing step for this kind of systems. In all my experience I used a lot of pre-processing functions to improve results. Simple functions like erode, dilate and smoothing to avoid noise in images are very useful in all Computer Vision projects. Afterwards, I found this book very useful and recommendable.
Overall, this is a must-read book for programmers, researchers, and people eager with basic OpenCV, Computer Vision and C++ knowledge.
This book is for people who have at least basic knowledge in OpenCV and Computer Vision, if you are new in OpenCV maybe this book won’t be the suitable one. Additionally all the examples are in C++ for Visual Studio, I did not like the last restriction, but it was necessary for some examples. This book show some upcoming OpenCV functions for the next release 3.0 (available at this time in Alpha version), and there are a lot of very useful functions.
Let’s begin with the main review. First chapters are about OpenCV basic functionalities (load images, brightness, contrast, color spaces, arithmetic and geometrical transforms). For every topic they show the code, explanation and results. The book shows tips in each topic, giving you the opportunity to investigate more about the functionality, and also they usually share links to Scientific Papers, thus, if you have a better idea to improve that function it helps you to do research about it.
I found Threshold topic in Chapter 4 (What’s in the Image? Segmentation) very useful and didactic, a lot of developers (also experts) made mistakes in this topic when choosing the type of threshold. Until here, Chapters were about main OpenCV functions, but here on-wards the book becomes better and very useful with content about Pattern Recognition, Classification, also Video Processing. Thus, I will discuss separated every chapter.
Chapter 5: Focusing on the Interesting 2D Features: This Chapter is totally based in Keypoints and its variations, the book provide a lot of examples and also the matching between images using Keypoints. Additionally some new OpenCV feature detectors of the new release are explained (KAZE and AKAZE).
Chapter 6: Where’s Wally? Object Detection: The main topics are Cascade detectors and Latent SVM. The book shows an example of basic pedestrian detection in a few lines of code using HOG cascade detector. Also, if you need to train your own cascade, you will find a detailed explanation about how to do it.
Chapter 7: What is he Doing? Motion: Due to I developed this kind of systems, I particularly liked this Chapter. Topics like Video tracking, Motion and Background subtraction are now included in the new OpenCV 3.0 and certainly will be very useful for everyone who is developing/researching this area. The book does not show the typical Optical Flow, but explains and optimized and faster Lucas-Kanade optical flow instead.
Chapter 8: Advanced Topics: If you are interested in Machine learning, Classification, or CUDA GPU programming this Chapter will be very useful too. It shows how to use the Random Forest classifier, one of the best classifiers available in recognition power and efficiency. Also the typical SVM is explained with a simple version of a recognition system.
To summarize, if you are using OpenCV for basic image processing certainly you will be more interested in Chapter 1 to 4, and maybe 5. If you need more depth knowledge and want to do complex Pattern Recognition systems you will be interested in Chapter 5 on-wards. The main weak point of this book is about pre-processing image explanation, although authors show some of them, they do not explain the real potential of the pre-processing step for this kind of systems. In all my experience I used a lot of pre-processing functions to improve results. Simple functions like erode, dilate and smoothing to avoid noise in images are very useful in all Computer Vision projects. Afterwards, I found this book very useful and recommendable.
Overall, this is a must-read book for programmers, researchers, and people eager with basic OpenCV, Computer Vision and C++ knowledge.
November 30, 2014
Sunitha P. from Packt Publishing provided me with a review e-copy of “OpenCV Essentials”. A book with many authors, most of which seem to be linked to the same university. The book has about 200 pages and the following 8 chapters:
Chapter 1, Getting Started is an introductory chapter, but it does require prior knowledge of OpenCV. In this and other chapters Windows users get the most detailed help.
Chapter 2, Something We Look At – Graphical User Interfaces goes deeper into GUI capabilities related to OpenCV.
Chapter 3, First Things First – Image Processing covers brightness control, contrast and color conversion, retina filtering, and geometrical transformations.
Chapter 4, What’s in the Image? Segmentation explains how to extract regions of interest within an image.
Chapter 5, Focusing on the Interesting 2D Features covers several feature detectors.
Chapter 6, Where’s Wally? Object Detection is about the OpenCV objdetect module for object detection.
Chapter 7, What Is He Doing? Motion covers techniques related to video and motion detection.
Chapter 8, Advanced Topics focuses on machine learning and GPUs (CUDA).
Although the book was written by multiple authors it’s not noticeable. I particularly liked the example where a picture of a baboon was transformed into the image of Lena Soderberg. Overall “OpenCV Essentials” was an enjoyable read.
Chapter 1, Getting Started is an introductory chapter, but it does require prior knowledge of OpenCV. In this and other chapters Windows users get the most detailed help.
Chapter 2, Something We Look At – Graphical User Interfaces goes deeper into GUI capabilities related to OpenCV.
Chapter 3, First Things First – Image Processing covers brightness control, contrast and color conversion, retina filtering, and geometrical transformations.
Chapter 4, What’s in the Image? Segmentation explains how to extract regions of interest within an image.
Chapter 5, Focusing on the Interesting 2D Features covers several feature detectors.
Chapter 6, Where’s Wally? Object Detection is about the OpenCV objdetect module for object detection.
Chapter 7, What Is He Doing? Motion covers techniques related to video and motion detection.
Chapter 8, Advanced Topics focuses on machine learning and GPUs (CUDA).
Although the book was written by multiple authors it’s not noticeable. I particularly liked the example where a picture of a baboon was transformed into the image of Lena Soderberg. Overall “OpenCV Essentials” was an enjoyable read.
November 16, 2014
Book is very good recipe for those who has prior knowledge of opencv, I did my engineering project using opencv so I was already familiar with this topic. Examples given in this book are for visual studio, but in first chapter it also explains how to use QT grphics library and integrating opecv with QT.
In 3rd Chapter book covers basic image types, fundamentals of image and data types used to represent an image. In segmentation chapter author explains algorithms with proper examples and pictures which helps alot in understanding segmentaion and it usability in image processing.
In Chapter 6 and 7 author describes SVM , Object detection algorithms and then how it works in OpenCV, This is what makes this book unique in its category.
I always wanted to know how can I use machine learning algorithms in opencv, I had basic idea of opencv but problem was from where to start. This is a book which answers all those basic questions.
We know that number of standard algorithms are already implemented in opencv but how can we use and what prior data is required to use those functions. This book genuinely helps to build concepts about opencv.
In 3rd Chapter book covers basic image types, fundamentals of image and data types used to represent an image. In segmentation chapter author explains algorithms with proper examples and pictures which helps alot in understanding segmentaion and it usability in image processing.
In Chapter 6 and 7 author describes SVM , Object detection algorithms and then how it works in OpenCV, This is what makes this book unique in its category.
I always wanted to know how can I use machine learning algorithms in opencv, I had basic idea of opencv but problem was from where to start. This is a book which answers all those basic questions.
We know that number of standard algorithms are already implemented in opencv but how can we use and what prior data is required to use those functions. This book genuinely helps to build concepts about opencv.
December 14, 2014
A few days ago, I read finished this book.
This book is really great.Thus there is my objective review.
This book is for people who have at least basic knowledge in OpenCV and Image Processing.I have read the book " Learning OpenCV" and other image processing books, So when I read this book, I fell very well.
This book I am most interested in is the Chapter 4,Chapter 5 and Chapter 6.I found Threshold topic in Chapter 4 very useful and didactic Help me solve some problems at work.
Chapter 5 is totally based in Keypoints and its variations, the book provide a lot of examples and also the matching between
images using Keypoints. Additionally some new OpenCV feature detectors of the new release are explained (KAZE and AKAZE). After reading this chapter, for understanding the FAST detector,SURF detector,ORB detector... are very helpful.
The main topics are Cascade detectors and Latent SVM in Chapter 6 . It's shows an example of basic pedestrian detection in a few lines of code using HOG cascade detector. Also, if you need to train your own cascade, you will find a detailed explanation about how to do it.
In short, this is a very good book, well worth reading.
This book is really great.Thus there is my objective review.
This book is for people who have at least basic knowledge in OpenCV and Image Processing.I have read the book " Learning OpenCV" and other image processing books, So when I read this book, I fell very well.
This book I am most interested in is the Chapter 4,Chapter 5 and Chapter 6.I found Threshold topic in Chapter 4 very useful and didactic Help me solve some problems at work.
Chapter 5 is totally based in Keypoints and its variations, the book provide a lot of examples and also the matching between
images using Keypoints. Additionally some new OpenCV feature detectors of the new release are explained (KAZE and AKAZE). After reading this chapter, for understanding the FAST detector,SURF detector,ORB detector... are very helpful.
The main topics are Cascade detectors and Latent SVM in Chapter 6 . It's shows an example of basic pedestrian detection in a few lines of code using HOG cascade detector. Also, if you need to train your own cascade, you will find a detailed explanation about how to do it.
In short, this is a very good book, well worth reading.
November 16, 2014
A short but efficient introduction to how to use OpenCV on any platform.
Most relevant topics (image processing, filtering, conversion, feature detection and description …) are addressed and illustrated with sample code. Every sample application is well commented and detailed, so as to get you started.
Beware, however, that this book is not aimed at teaching you the fundamentals of image processing or computer vision. Its only aim is to help you process images and videos using OpenCV 2 (mostly, but with glimpses on the forthcoming OpenCV 3). Undoubtedly, it reaches its goal. However, people intending to invest heavily in OpenCV might hesitate between this book and, for example, Robert Laganière's book "OpenCV Computer Vision Application Programming Cookbook, 2nd Edition" (also from PacktPub).
Both are good choices. The Cookbook is almost twice as large; Essentials is shorter but is the only of the two that refers partly to OpenCV 3 and that also deals with the CUDA-supported implementation of OpenCV.
A recommended reading, in any case!
Most relevant topics (image processing, filtering, conversion, feature detection and description …) are addressed and illustrated with sample code. Every sample application is well commented and detailed, so as to get you started.
Beware, however, that this book is not aimed at teaching you the fundamentals of image processing or computer vision. Its only aim is to help you process images and videos using OpenCV 2 (mostly, but with glimpses on the forthcoming OpenCV 3). Undoubtedly, it reaches its goal. However, people intending to invest heavily in OpenCV might hesitate between this book and, for example, Robert Laganière's book "OpenCV Computer Vision Application Programming Cookbook, 2nd Edition" (also from PacktPub).
Both are good choices. The Cookbook is almost twice as large; Essentials is shorter but is the only of the two that refers partly to OpenCV 3 and that also deals with the CUDA-supported implementation of OpenCV.
A recommended reading, in any case!
September 28, 2014
I received a copy of this from the publisher, and I am very glad I did. It's a wonderful book for everyone who wants to get fast solid knowledge of OpenCV.
I have done Image processing in my University program and if I had the book at that time, the course would be much more easy and interesting primarily because "OpenCV Essentials" delivers all information in a straightforward way supported by lots of examples. The book is perfect for people with basic C++ knowledge who want to dwelve in the deeps of OpenCV with no complications like advanced mathematics and programming. I found it a pleasure to dip into different sections of the book with no previous knowledge of the topic.
I would recommend the book to all newcomers in OpenCV.
I have done Image processing in my University program and if I had the book at that time, the course would be much more easy and interesting primarily because "OpenCV Essentials" delivers all information in a straightforward way supported by lots of examples. The book is perfect for people with basic C++ knowledge who want to dwelve in the deeps of OpenCV with no complications like advanced mathematics and programming. I found it a pleasure to dip into different sections of the book with no previous knowledge of the topic.
I would recommend the book to all newcomers in OpenCV.
November 10, 2014
First things first, OpenCV Essentials is definitely not a book for an image processing/computer vision novice.If you’ve been using OpenCV and programming in C++ for at least a few months and want a resource which you can quickly refer to when you’re delving into some of the deeper functionality of OpenCV, then I can thoroughly recommend this book to you.I’ve been using OpenCV for about one and a half years, and over that time I have witnessed a definite improvement in the documentation available online. However, good examples of some of the deeper functionality are still difficult to come across, and the ability of this book to plug this gap is one of its chief virtues.
September 29, 2014
\o/ A good introduction to computer vision using OpenCV. I wish I had this book two years ago :)
Displaying 1 - 9 of 9 reviews