Real-time and low-cost embedded platform for car's surrounding vision system

The design and the implementation of a flexible and low-cost embedded system for real-time car's surrounding vision is presented. The target of the proposed multi-camera vision system is to provide the driver a better view of the objects that surround the vehicle. Fish-eye lenses are used to achieve a larger Field of View (FOV) but, on the other hand, introduce radial distortion of the images projected on the sensors. Using low-cost cameras there could be also some alignment issues. Since these complications are noticeable and dangerous, a real-time algorithm for their correction is presented. Then another real-time algorithm, used for merging 4 camera video streams together in a single view, is described. Real-time image processing is achieved through a hardware-software platform

Real-time multi-camera video acquisition and processing platform for ADAS

The paper presents the design of a real-time and low-cost embedded system for image acquisition and processing in Advanced Driver Assisted Systems (ADAS). The system adopts a multi-camera architecture to provide a panoramic view of the objects surrounding the vehicle. Fish-eye lenses are used to achieve a large Field of View (FOV). Since they introduce radial distortion of the images projected on the sensors, a real-time algorithm for their correction is also implemented in a pre-processor. An FPGA-based hardware implementation, re-using IP macrocells for several ADAS algorithms, allows for real-time processing of input streams from VGA automotive CMOS cameras