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)


In this chapter, you learned how an Automatic Number Plate Recognition program works and its two important steps: plate localization and plate recognition.

In the first step, you learned how to segment an image by looking for patches where we may have a plate, and using simple heuristics and the SVM algorithm to make a binary classification for patches with plates and no plates.

In the second step, you learned how to segment using the find contours algorithm, create a deep learning model with TensorFlow, and train and import it into OpenCV. You also learned how to increase the number of samples in your dataset using augmentation techniques.

In the next chapter, you will learn how to create a face recognition application using eigenfaces and deep learning.