الفهرس 
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Abstract
Real time processing of image and video applications, especially
Augmented Reality (AR) systems is a demand in many computer vision
applications, e.g. video surveillance, traffic management and medical
imaging. Augmented Reality (AR) is divided into vision processing
engine and graphics processing engine. Those two processing engines use
highly computational intensive tasks such as image segmentation, object
recognition, and feature tracking. The processing of those functions
requires high computational power, especially when they are applied on
high-definition (HD) input video frames. The processing of video and
image algorithms of real time AR is not capable of running on devices
efficiently with low computing power at a reasonable frame rate. The
collaboration of the CPU and hardware accelerators provides an efficient
solution for this problem.In this thesis, the presented approach targets offloading highlycomputational pixel processing modules from processing system (PS) toprogrammable logic (PL) taking the advantage of High Level Synthesis
(HLS) tool flow to accelerate the implementation of compute-intensivepixel processing tasks of AR. Hardware accelerators for AR processingtasks are proposed. The accelerators are applied on full HD video inputstream at 1080p60 of HDMI input. The performance improvementthrough hardware acceleration decreases the CPU utilization andincreases the frame rate.