|
Showing 1 - 6 of
6 matches in All Departments
Delve into practical computer vision and image processing projects
and get up to speed with advanced object detection techniques and
machine learning algorithms Key Features Discover best practices
for engineering and maintaining OpenCV projects Explore important
deep learning tools for image classification Understand basic image
matrix formats and filters Book DescriptionOpenCV is one of the
best open source libraries available and can help you focus on
constructing complete projects on image processing, motion
detection, and image segmentation. This Learning Path is your guide
to understanding OpenCV concepts and algorithms through real-world
examples and activities. Through various projects, you'll also
discover how to use complex computer vision and machine learning
algorithms and face detection to extract the maximum amount of
information from images and videos. In later chapters, you'll learn
to enhance your videos and images with optical flow analysis and
background subtraction. Sections in the Learning Path will help you
get to grips with text segmentation and recognition, in addition to
guiding you through the basics of the new and improved deep
learning modules. By the end of this Learning Path, you will have
mastered commonly used computer vision techniques to build OpenCV
projects from scratch. This Learning Path includes content from the
following Packt books: Mastering OpenCV 4 - Third Edition by Roy
Shilkrot and David Millan Escriva Learn OpenCV 4 By Building
Projects - Second Edition by David Millan Escriva, Vinicius G.
Mendonca, and Prateek Joshi What you will learn Stay up-to-date
with algorithmic design approaches for complex computer vision
tasks Work with OpenCV's most up-to-date API through various
projects Understand 3D scene reconstruction and Structure from
Motion (SfM) Study camera calibration and overlay augmented reality
(AR) using the ArUco module Create CMake scripts to compile your
C++ application Explore segmentation and feature extraction
techniques Remove backgrounds from static scenes to identify moving
objects for surveillance Work with new OpenCV functions to detect
and recognize text with Tesseract Who this book is forIf you are a
software developer with a basic understanding of computer vision
and image processing and want to develop interesting computer
vision applications with OpenCV, this Learning Path is for you.
Prior knowledge of C++ and familiarity with mathematical concepts
will help you better understand the concepts in this Learning Path.
Work on practical computer vision projects covering advanced object
detector techniques and modern deep learning and machine learning
algorithms Key Features Learn about the new features that help
unlock the full potential of OpenCV 4 Build face detection
applications with a cascade classifier using face landmarks Create
an optical character recognition (OCR) model using deep learning
and convolutional neural networks Book DescriptionMastering OpenCV,
now in its third edition, targets computer vision engineers taking
their first steps toward mastering OpenCV. Keeping the mathematical
formulations to a solid but bare minimum, the book delivers
complete projects from ideation to running code, targeting current
hot topics in computer vision such as face recognition, landmark
detection and pose estimation, and number recognition with deep
convolutional networks. You'll learn from experienced OpenCV
experts how to implement computer vision products and projects both
in academia and industry in a comfortable package. You'll get
acquainted with API functionality and gain insights into design
choices in a complete computer vision project. You'll also go
beyond the basics of computer vision to implement solutions for
complex image processing projects. By the end of the book, you will
have created various working prototypes with the help of projects
in the book and be well versed with the new features of OpenCV4.
What you will learn Build real-world computer vision problems with
working OpenCV code samples Uncover best practices in engineering
and maintaining OpenCV projects Explore algorithmic design
approaches for complex computer vision tasks Work with OpenCV's
most updated API (v4.0.0) through projects Understand 3D scene
reconstruction and Structure from Motion (SfM) Study camera
calibration and overlay AR using the ArUco Module Who this book is
forThis book is for those who have a basic knowledge of OpenCV and
are competent C++ programmers. You need to have an understanding of
some of the more theoretical/mathematical concepts, as we move
quite quickly throughout the book.
Discover interesting recipes to help you understand the concepts of
object detection, image processing, and facial detection Key
Features Explore the latest features and APIs in OpenCV 4 and build
computer vision algorithms Develop effective, robust, and fail-safe
vision for your applications Build computer vision algorithms with
machine learning capabilities Book DescriptionOpenCV is an image
and video processing library used for all types of image and video
analysis. Throughout the book, you'll work through recipes that
implement a variety of tasks, such as facial recognition and
detection. With 70 self-contained tutorials, this book examines
common pain points and best practices for computer vision (CV)
developers. Each recipe addresses a specific problem and offers a
proven, best-practice solution with insights into how it works, so
that you can copy the code and configuration files and modify them
to suit your needs. This book begins by setting up OpenCV, and
explains how to manipulate pixels. You'll understand how you can
process images with classes and count pixels with histograms.
You'll also learn detecting, describing, and matching interest
points. As you advance through the chapters, you'll get to grips
with estimating projective relations in images, reconstructing 3D
scenes, processing video sequences, and tracking visual motion. In
the final chapters, you'll cover deep learning concepts such as
face and object detection. By the end of the book, you'll be able
to confidently implement a range to computer vision algorithms to
meet the technical requirements of your complex CV projects What
you will learn Install and create a program using the OpenCV
library Segment images into homogenous regions and extract
meaningful objects Apply image filters to enhance image content
Exploit image geometry to relay different views of a pictured scene
Calibrate the camera from different image observations Detect
people and objects in images using machine learning techniques
Reconstruct a 3D scene from images Explore face detection using
deep learning Who this book is forIf you're a CV developer or
professional who already uses or would like to use OpenCV for
building computer vision software, this book is for you. You'll
also find this book useful if you're a C++ programmer looking to
extend your computer vision skillset by learning OpenCV.
Explore OpenCV 4 to create visually appealing cross-platform
computer vision applications Key Features Understand basic OpenCV 4
concepts and algorithms Grasp advanced OpenCV techniques such as 3D
reconstruction, machine learning, and artificial neural networks
Work with Tesseract OCR, an open-source library to recognize text
in images Book DescriptionOpenCV is one of the best open source
libraries available, and can help you focus on constructing
complete projects on image processing, motion detection, and image
segmentation. Whether you're completely new to computer vision, or
have a basic understanding of its concepts, Learn OpenCV 4 by
Building Projects - Second edition will be your guide to
understanding OpenCV concepts and algorithms through real-world
examples and projects. You'll begin with the installation of OpenCV
and the basics of image processing. Then, you'll cover user
interfaces and get deeper into image processing. As you progress
through the book, you'll learn complex computer vision algorithms
and explore machine learning and face detection. The book then
guides you in creating optical flow video analysis and background
subtraction in complex scenes. In the concluding chapters, you'll
also learn about text segmentation and recognition and understand
the basics of the new and improved deep learning module. By the end
of this book, you'll be familiar with the basics of Open CV, such
as matrix operations, filters, and histograms, and you'll have
mastered commonly used computer vision techniques to build OpenCV
projects from scratch. What you will learn Install OpenCV 4 on your
operating system Create CMake scripts to compile your C++
application Understand basic image matrix formats and filters
Explore segmentation and feature extraction techniques Remove
backgrounds from static scenes to identify moving objects for
surveillance Employ various techniques to track objects in a live
video Work with new OpenCV functions for text detection and
recognition with Tesseract Get acquainted with important deep
learning tools for image classification Who this book is forIf you
are a software developer with a basic understanding of computer
vision and image processing and want to develop interesting
computer vision applications with OpenCV, Learn OpenCV 4 by
Building Projects for you. Prior knowledge of C++ will help you
understand the concepts covered in this book.
Practical Computer Vision Projects About This Book * Updated for
OpenCV 3, this book covers new features that will help you unlock
the full potential of OpenCV 3 * Written by a team of 7 experts,
each chapter explores a new aspect of OpenCV to help you make
amazing computer-vision aware applications * Project-based approach
with each chapter being a complete tutorial, showing you how to
apply OpenCV to solve complete problems Who This Book Is For This
book is for those who have a basic knowledge of OpenCV and are
competent C++ programmers. You need to have an understanding of
some of the more theoretical/mathematical concepts, as we move
quite quickly throughout the book. What You Will Learn * Execute
basic image processing operations and cartoonify an image * Build
an OpenCV project natively with Raspberry Pi and cross-compile it
for Raspberry Pi.text * Extend the natural feature tracking
algorithm to support the tracking of multiple image targets on a
video * Use OpenCV 3's new 3D visualization framework to illustrate
the 3D scene geometry * Create an application for Automatic Number
Plate Recognition (ANPR) using a support vector machine and
Artificial Neural Networks * Train and predict pattern-recognition
algorithms to decide whether an image is a number plate * Use POSIT
for the six degrees of freedom head pose * Train a face recognition
database using deep learning and recognize faces from that database
In Detail As we become more capable of handling data in every kind,
we are becoming more reliant on visual input and what we can do
with those self-driving cars, face recognition, and even augmented
reality applications and games. This is all powered by Computer
Vision. This book will put you straight to work in creating
powerful and unique computer vision applications. Each chapter is
structured around a central project and deep dives into an
important aspect of OpenCV such as facial recognition, image target
tracking, making augmented reality applications, the 3D
visualization framework, and machine learning. You'll learn how to
make AI that can remember and use neural networks to help your
applications learn. By the end of the book, you will have created
various working prototypes with the projects in the book and will
be well versed with the new features of OpenCV3. Style and approach
This book takes a project-based approach and helps you learn about
the new features by putting them to work by implementing them in
your own projects.
Enhance your understanding of Computer Vision and image processing
by developing real-world projects in OpenCV 3 About This Book * Get
to grips with the basics of Computer Vision and image processing *
This is a step-by-step guide to developing several real-world
Computer Vision projects using OpenCV 3 * This book takes a special
focus on working with Tesseract OCR, a free, open-source library to
recognize text in images Who This Book Is For If you are a software
developer with a basic understanding of Computer Vision and image
processing and want to develop interesting Computer Vision
applications with Open CV, this is the book for you. Knowledge of
C++ is required. What You Will Learn * Install OpenCV 3 on your
operating system * Create the required CMake scripts to compile the
C++ application and manage its dependencies * Get to grips with the
Computer Vision workflows and understand the basic image matrix
format and filters * Understand the segmentation and feature
extraction techniques * Remove backgrounds from a static scene to
identify moving objects for video surveillance * Track different
objects in a live video using various techniques * Use the new
OpenCV functions for text detection and recognition with Tesseract
In Detail Open CV is a cross-platform, free-for-use library that is
primarily used for real-time Computer Vision and image processing.
It is considered to be one of the best open source libraries that
helps developers focus on constructing complete projects on image
processing, motion detection, and image segmentation. Whether you
are completely new to the concept of Computer Vision or have a
basic understanding of it, this book will be your guide to
understanding the basic OpenCV concepts and algorithms through
amazing real-world examples and projects. Starting from the
installation of OpenCV on your system and understanding the basics
of image processing, we swiftly move on to creating optical flow
video analysis or text recognition in complex scenes, and will take
you through the commonly used Computer Vision techniques to build
your own Open CV projects from scratch. By the end of this book,
you will be familiar with the basics of Open CV such as matrix
operations, filters, and histograms, as well as more advanced
concepts such as segmentation, machine learning, complex video
analysis, and text recognition. Style and approach This book is a
practical guide with lots of tips, and is closely focused on
developing Computer vision applications with OpenCV. Beginning with
the fundamentals, the complexity increases with each chapter.
Sample applications are developed throughout the book that you can
execute and use in your own projects.
|
You may like...
Loot
Nadine Gordimer
Paperback
(2)
R398
R330
Discovery Miles 3 300
|