Book Image

Mastering OpenCV 4 - Third Edition

By : Roy Shilkrot, David Millán Escrivá
Book Image

Mastering OpenCV 4 - Third Edition

By: Roy Shilkrot, David Millán Escrivá

Overview of this book

Mastering 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.
Table of Contents (12 chapters)

Historic algorithms in OpenCV

When starting to work on an OpenCV project, one should be aware of its historical past. OpenCV has existed for more than 15 years as an open source project, and despite its very dedicated management team that aims to better the library and keep it relevant, some implementations are more outdated than others. Some APIs are left for backward compatibility with previous versions, and others are targeted at specific algorithmic circumstances, all while newer algorithms are added.

Any engineer looking to choose the best performing algorithm for his work should have the tools to inquire about a specific algorithm to see when it was added and what are its origins (for example, a research paper). That is not to suggest that anything new is necessarily better, as some basic and older algorithms are excellent performers, and in most cases there's a clear...