Basic Computer Vision Operations Using OpenCV and CUDA

The last chapter described the process of working with images and videos using OpenCV and CUDA. We looked at the code for some basic image and video processing applications and compared the performance of OpenCV code with and without CUDA acceleration. In this chapter, we will build on this knowledge and try to develop some more computer vision and image processing applications using OpenCV and CUDA. This chapter describes the method for accessing individual pixel intensities in color and grayscale images. A histogram is a very useful concept for image processing. This chapter describes the method for calculating histograms and how histogram equalization can improve the visual quality of images. This chapter will also describe how different geometric transformations can be performed using OpenCV and CUDA. Image filtering is...