Low complexity real-time feature extraction, using image projections

In this paper it is shown how low complexity image projections can be used to replace the much more memory demanding functions morphology and labeling. The image projections are intended to be used in an automatic real-time surveillance system to detect objects and extract features. The projection unit operates directly on the binary motion mask from the segmentation unit and can extract location, size and center of gravity of the detected objects. To increase the precision, multiple projections are calculated in the Y-direction of the motion mask. To verify the design a demonstrator has been implemented on a Xilinx FPGA, where the effect of different input settings can be evaluated in real-time. Compared to the previous solution with morphology and labeling, the memory requirement is reduced from O(n ²) to O(n).