The performance of image processing algorithms can be measured in terms of the time it takes to process a single image. When algorithms work on video, performance is measured in terms of frames per second, which indicates the number of frames it can process in a second. When the algorithm can process more than 30 frames per second, it can be considered to work in real time. We can also measure the performance of our algorithms implemented in OpenCV, which will be discussed in this section.
As we discussed earlier, when OpenCV is built with CUDA compatibility, it can increase the performance of algorithms drastically. OpenCV functions in the CUDA module are optimized to utilize GPU parallel processing capability. OpenCV also provides similar functions that only run on CPU. In this section, we will compare...
