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Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA

You're reading from   Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA Effective techniques for processing complex image data in real time using GPUs

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789348293
Length 380 pages
Edition 1st Edition
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Author (1):
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Bhaumik Vaidya Bhaumik Vaidya
Author Profile Icon Bhaumik Vaidya
Bhaumik Vaidya
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Table of Contents (15) Chapters Close

Preface 1. Introducing CUDA and Getting Started with CUDA 2. Parallel Programming using CUDA C FREE CHAPTER 3. Threads, Synchronization, and Memory 4. Advanced Concepts in CUDA 5. Getting Started with OpenCV with CUDA Support 6. Basic Computer Vision Operations Using OpenCV and CUDA 7. Object Detection and Tracking Using OpenCV and CUDA 8. Introduction to the Jetson TX1 Development Board and Installing OpenCV on Jetson TX1 9. Deploying Computer Vision Applications on Jetson TX1 10. Getting Started with PyCUDA 11. Working with PyCUDA 12. Basic Computer Vision Applications Using PyCUDA 13. Assessments 14. Other Books You May Enjoy

Summary

In this chapter, we started with the introduction of computer vision and image processing. We described OpenCV library, which is specifically made for computer vision applications, and how it is different from other computer vision software. OpenCV can leverage the parallel processing capability of GPU by using CUDA. We looked at the installation procedure for OpenCV with CUDA in all operating systems. We described the process to read an image from disk, display it on screen, and save it back to disk. Videos are nothing more than a sequence of images. We learned to work with videos from disk as well as videos captured from camera. We developed several image processing applications that do different operations on images, such as arithmetic operations, logical operations, color space conversions, and thresholding. In the last section, we compared the performance of the...

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