Qt 5 and OpenCV 4 Computer Vision Projects

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Publisher ‏ : ‎ Packt Publishing (June 20, 2019)
Language ‏ : ‎ English
Paperback ‏ : ‎ 348 pages
ISBN-10 ‏ : ‎ 1789532582
ISBN-13 ‏ : ‎ 978-1789532586
Item Weight ‏ : ‎ 1.34 pounds
Dimensions ‏ : ‎ 9.25 x 7.52 x 0.73 inches

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In this post, we will discuss some exciting projects that combine the power of Qt 5 and OpenCV 4 for computer vision applications. Qt is a popular cross-platform application framework that allows developers to create user interfaces for desktop, mobile, and embedded platforms. OpenCV is an open-source computer vision library that provides a wide range of algorithms for image processing, object detection, and machine learning.

One project that can be created using Qt 5 and OpenCV 4 is a real-time face detection and recognition system. This project can use the Haar cascades algorithm provided by OpenCV for face detection, and a machine learning algorithm like Eigenfaces or Fisherfaces for face recognition. The user interface can be built using Qt 5 to display the live video feed from the camera and highlight detected faces with bounding boxes.

Another interesting project is a license plate recognition system using Qt 5 and OpenCV 4. This project can use the Tesseract OCR engine provided by OpenCV for optical character recognition of license plates in images or video streams. The user interface can display the recognized license plate numbers along with additional information like the date and time of detection.

These are just a few examples of the many computer vision projects that can be created using Qt 5 and OpenCV 4. By combining the powerful features of these two libraries, developers can create sophisticated applications for image processing, object detection, and machine learning. If you are interested in exploring the possibilities of computer vision, consider trying out these projects and experimenting with the capabilities of Qt 5 and OpenCV 4.
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