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)

Number Plate Recognition with Deep Convolutional Networks

This chapter introduces us to the steps needed to create an application for Automatic Number Plate Recognition (ANPR). There are different approaches and techniques based on different situations; for example, an infrared camera, fixed car position, and light conditions. We can proceed to construct an ANPR application to detect automobile license plates in a photograph taken between two and three meters from a car, in ambiguous light conditions, and with a non-parallel ground with minor perspective distortions in the automobile's plate.

The main purpose of this chapter is to introduce us to image segmentation and feature extraction, pattern recognition basics, and two important pattern recognition algorithms, the Support Vector Machine (SVM) and deep neural network (DNN), using convolutional networks. In this chapter...