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Hands-On Algorithms for Computer Vision
Hands-On Algorithms for Computer Vision

Hands-On Algorithms for Computer Vision: Learn how to use the best and most practical computer vision algorithms using OpenCV by Amin Ahmadi Tazehkandi
English | 27 July 2018 | ISBN: 1789130948 | 290 Pages | EPUB | 9.37 MB

Create powerful, accurate, and real-time Computer Vision applications using a perfect blend of algorithms and filters. Also learn about object tracking and foreground extractions with a variety of new filters and algorithms.


Key Features
Filter, transform, and manipulate images using MAT class and OpenCV Framework
Explore motion detection and object tracking with filters and algorithms
Build object detectors using deep learning and machine learning algorithms
Book Description
An arena that has been positively impacted by the advancements in processing power and performance is the field of computer vision. It's only natural that over time, more and more algorithms are introduced to perform computer vision tasks more efficiently. Hands-On Algorithms for Computer Vision is a starting point for anyone who is interested in the field of computer vision and wants to explore the most practical algorithms used by professional computer vision developers. The book starts with the basics and builds up over the course of the chapters with hands-on examples for each algorithm.

Right from the start, you will learn about the required tools for computer vision development, and how to install and configure them. You'll explore the OpenCV framework and its powerful collection of libraries and functions. Starting from the most simple image modifications, filtering, and transformations, you will gradually build up your knowledge of various algorithms until you are able to perform much more sophisticated tasks, such as real-time object detection using deep learning algorithms.

What you will learn
Get to grips with machine learning and artificial intelligence algorithms
Read, write, and process images and videos
Perform mathematical, matrix, and other types of image data operations
Create and use histograms from back-projection images
Detect motion, extract foregrounds, and track objects
Extract key points with a collection of feature detector algorithms
Develop cascade classifiers and use them, and train and test classifiers
Employ TensorFlow object detection to detect multiple objects
Who this book is for
Hands-On Algorithms for Computer Vision helps those who want to learn algorithms in Computer Vision to create and customize their applications. This book will also help existing Computer Vision developers customize their applications. A basic understanding of computer vision and programming experience is needed.

Table of Contents
Introduction to Computer Vision
Getting Started with OpenCV
Array and Matrix Operations
Drawing, Filtering, and Transformation
Back-Projection and Histograms
Video Analysis - Motion Detection and Tracking
Object Detection - Features and Descriptors
Machine Learning in Computer Vision
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