The current robots follow clear, repetitive and logical instructions, but generally, they have problems in managing unstructured environments and reacting dynamically to these. Thus, modern robots require improved vision systems capable of obtaining information about such environments at a high acquisition rate and with high processing speeds. The growing demand for robotic platforms, both industrial and mobile, has greatly boosted the development of advanced vision systems. A weak point of traditional computer vision is that it depends on algorithms executed on a computer or server connected to the robot, often involving the need for high computing resources. Therefore, much of the efforts of the last decades have been focused on the improvement of those algorithms. Nevertheless, when the limit of traditional software processing systems (PCs, microcontrollers and microprocessors) is reached, it is necessary to migrate to a more versatile platform -which generally leads to hardware solutions-. The HW/SW design is possible because of high-frequency bridges between the Hard-Processor System (HPS) and the FPGA. Commonly, the most demanding tasks of the image processing are made in the FPGA, whereas the HPS handles the processed data and performs the high-level control function. This work presents a proposal for HW/SW integration using a SoC FPGA, for the images processing provided by the Intel Realsense®3D camera (an RGB-D sensor). This approach seeks to enhance the streamlining and filtering stages to obtain faster results compared to a traditional system.