Book Image

OpenCV 3.x with Python By Example - Second Edition

By : Gabriel Garrido Calvo, Prateek Joshi
Book Image

OpenCV 3.x with Python By Example - Second Edition

By: Gabriel Garrido Calvo, Prateek Joshi

Overview of this book

Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples. This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications.
Table of Contents (17 chapters)
Title Page
Copyright and Credits
Packt Upsell

Machine learning (ML) versus artificial neural network (ANN)

As mentioned earlier, an ANN is a subset of ML. ANNs are inspired by human understanding; they work as our brain does, composed of different interconnected layers of neurons, where each of them receives information from previous one, processes it, and sends it to the next one until the final output is received. This output could be from a labeled output in the case of supervised learning or certain criteria matching in the case of unsupervised learning.

What are the peculiarities of an ANN? Machine learning is defined as the area in computer science that focuses on trying to find patterns within data sets, and ANN is more oriented toward simulating how human brains are connected to make that work, splitting pattern detection across several layers/nodes that we will call neurons.

Meanwhile, other machine learning algorithms such as support vector machine (SVM) are more popular and established on the object pattern recognition and...