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OPENCV BY EXAMPLE
Título:
OPENCV BY EXAMPLE
Subtítulo:
Autor:
JOSHI, P
Editorial:
PACKT PUBLISHING
Año de edición:
2016
Materia
VISION POR ORDENADOR
ISBN:
978-1-78528-094-8
Páginas:
296
49,50 €

 

Sinopsis

Book Description

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.

Table of Contents

1: GETTING STARTED WITH OPENCV
2: AN INTRODUCTION TO THE BASICS OF OPENCV
3: LEARNING THE GRAPHICAL USER INTERFACE AND BASIC FILTERING
4: DELVING INTO HISTOGRAMS AND FILTERS
5: AUTOMATED OPTICAL INSPECTION, OBJECT SEGMENTATION, AND DETECTION
6: LEARNING OBJECT CLASSIFICATION
7: DETECTING FACE PARTS AND OVERLAYING MASKS
8: VIDEO SURVEILLANCE, BACKGROUND MODELING, AND MORPHOLOGICAL OPERATIONS
9: LEARNING OBJECT TRACKING
10: DEVELOPING SEGMENTATION ALGORITHMS FOR TEXT RECOGNITION
11: TEXT RECOGNITION WITH TESSERACT
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