Sign Detection System for Real Time Applications
We are designing a system that will detect stop signs in real time. To do this we are implementing a common object detection algorithm called Histogram of Oriented Gradients, and a common classification algorithm called Support Vector Machine. These two algorithms will work together to classify HD images as containing a stop sign or not containing a stop sign. Image processing can often be very slow for normal computers because modern images are often very big. To speed up the detection rate of our algorithm we chose to use a System on a Chip (SoC) device. This device allows us to implement some parts of the algorithm on a Field Programmable Gate Array (FPGA) and other parts on a Hard Processor System (HPS). Because both of these systems are on the same chip, there is a very fast communication speed between the two systems. Using both both an FPGA and a HPS we can significantly speed up the detection time of the HOG and SVM algorithms.
This harmony between hardware and software will allow us to detect stop signs in real time. This means that as the camera is recording the algorithm can determine if a frame has a stop sign in it before the next frame is captured. Real time system such as there are very important in high speed applications such as semi-autonomous and driver assisted cars. These cars need to be able to detect objects in their path at high speeds, and very high accuracy rates.