Most of the embedded products designed today are Vision-based systems with camera as a main component for its implementation. The cameras with wide angle lens enable them to capture images giving high-level descriptions of the scene useful for several applications, such as video surveillance, motion analysis, human/object detection, etc. However, images obtained using these wide angle lenses tend to be distorted causing straight lines from the scene to appear as curves in the image plane termed to be as Barrel or Radial Lens Distortion. Such distortion produces less realistic images and affects objects relative sizes, depending on their position in the image. It may be still acceptable in fisheye images, but in fisheye videos, the resulting distortion renders them hard to understand and uncomfortable to watch. It is therefore desirable to correct the barrel distorted images/video before presenting to the end viewer. A lot of research on algorithm that corrects for the distortion of the lens has been done to resolve this problem of radial distortion. Implementing this correction algorithm on a hardware platform can help in developing an ASIC that could be embedded into these Vision-based systems. In this paper, the authors review a framework to correct a wide angle lens distortion based on rectilinear and polynomial based model. The MATLAB implementation of these Distortion correction algorithms is done and comparison of their result is made. It is observed that rectilinear model gives efficient results as compared to polynomial based approach. The hardware platforms used to implement these algorithms are also been discussed. The analysis of these platforms suggest the advanced FPGAs (Field Programmable Gate Arrays) with embedded DSP blocks as a good choice for implementing these Barrel distortion correction algorithms for real time video capturing systems using wide angle lenses making it distortion free.