OpenCV means Open Source Computer Vision Library. It is software library that implement many popular Image Processing, Computer Vision and machine learning algorithms.
Modello di un miscelatore a convezione con,Fluido entrante ad entalpia costante e Contenitore metallico isolato termicamemte. Viene clacolata la dinamica tra le portate entrate ed uscente e il livello e temperatura del liquido.
Modello analitico dettagliato di uno scambiatore di calore metallico con fluido interno incomprimibile (liquido): la sua densità è costante;fluido esterno a capacità termica infinita: la sua temperatura Te non dipende dal calore scambiato ed è impostata.
Here is shown that both cv::Mat and Standard Library Containers work under memory recycling. We found that using std:queue as buffer for OpenCV Mat, memory requirements depends on size of the queue. We conclude that containers like std::queue can be used effectively as buffer for OpenCV Mats.
In Memory Analysis-Part 1 we conclude that a std::queue of OpenCV Mats is memory effective. Here is a real test case of our pkQueueTS with one grabber and one processor threads. We will perform memory analysis to validate our preliminary conclusion about memory effectiveness and recycling.
Working as vision systems integrator usually you will have need to acquire and save great numbers of fames or video sequence on field, in order to perform a later processing or studies. In this cases it’s vital to store the image “as is” without alteration. This may be is not a problem if you use raw image format like bmp or xpm but you can’t use JPG/PNG or DiVx/MPEGn because image/video compression forma are quality lossy. A good solution is to use Lossless image format like JPG2000 or Lagarith lossless codec to have a good compression without loosing information.
This page shows some lossless codec, how to install and use it with OpenCV image library