In my thesis I show the apparatus of the dusty plasma experiment.
During the experiment the particles form a crystalline structure and image sequences are taken of them with a high speed camera.
Processing these images results in the particle's positions and statistical distributions of the system.
I describe the detection procedure of the particles using filtering and adaptive decision level determination.
Instead of using the common and trivial FIR Gauss filter I propose and implement the more efficient median filter.
For computing the particle's position I implement the momentum method,
which is computationally more demanding but it provides sub-pixel resolution.
I give an overview of the OpenCL framework, which is used for parallel programming.
Applying the above introduced framework and taking into account the properties of the devices available I have composed the
program's principle steps.
These steps are optimized to achieve fast run times.
I benchmark the program's performance on CPU, on GPU and on many integrated core (MIC) card.
Finally I combine the program with the image acquiring software of the high speed camera for online image processing.