Book Image

Qt 5 and OpenCV 4 Computer Vision Projects

By : Zhuo Qingliang
4 (1)
Book Image

Qt 5 and OpenCV 4 Computer Vision Projects

4 (1)
By: Zhuo Qingliang

Overview of this book

OpenCV and Qt have proven to be a winning combination for developing cross-platform computer vision applications. By leveraging their power, you can create robust applications with both an intuitive graphical user interface (GUI) and high-performance capabilities. This book will help you learn through a variety of real-world projects on image processing, face and text recognition, object detection, and high-performance computing. You’ll be able to progressively build on your skills by working on projects of increasing complexity. You’ll begin by creating an image viewer application, building a user interface from scratch by adding menus, performing actions based on key-presses, and applying other functions. As you progress, the book will guide you through using OpenCV image processing and modification functions to edit an image with filters and transformation features. In addition to this, you’ll explore the complex motion analysis and facial landmark detection algorithms, which you can use to build security and face detection applications. Finally, you’ll learn to use pretrained deep learning models in OpenCV and GPUs to filter images quickly. By the end of this book, you will have learned how to effectively develop full-fledged computer vision applications with OpenCV and Qt.
Table of Contents (11 chapters)

Optical Character Recognition

In the previous chapters, we did a lot of work with videos and cameras. We created applications (Gazer and Facetious) with which we can play video from webcams attached to our computers. We can also record videos, take photos, detect motion and faces, and apply masks to faces detected in the video feed in real time with these apps.

Now we will move our focus to the text in images. There are many situations in which we want to extract the text or characters from an image. In the area of computer vision, there is a technology called Optical Character Recognition (OCR) to do this kind of work automatically instead of transcribing the text manually. In this chapter, we will build a new application to extract text from images and scanned documents with Qt and a number of OCR libraries.

We will cover the following topics in this chapter:

  • Extracting text...