Estimating parametric curves from images using robust fitting algorithms is a well-known and important computer vision task. We present a complete FPGA design and implementation of a fast and robust model fitting algorithm for real-time ellipse detection on video streams. The proposed solution relies on a the RANSAC algorithm, modified for FPGA deployment, in combination with an image-preprocessing pipeline in order to perform the intensive pixel-level analysis, reducing each frame to a simple binary image of edges. The design has been developed in a parallel fashion and with specific architectural solutions so as to allow a fast response without degrading the functional performances. Experimental results on synthetic and real data show that our implementation, synthesized onto a Xilinx Spartan-3A DSP 3400A device, succesfully runs in real-time with a low resource occupation, while maintaining a functionality comparable with the floating-point software version.
FPGA-based robust ellipse estimation for circular road sign detection
MURINO, Vittorio
2010-01-01
Abstract
Estimating parametric curves from images using robust fitting algorithms is a well-known and important computer vision task. We present a complete FPGA design and implementation of a fast and robust model fitting algorithm for real-time ellipse detection on video streams. The proposed solution relies on a the RANSAC algorithm, modified for FPGA deployment, in combination with an image-preprocessing pipeline in order to perform the intensive pixel-level analysis, reducing each frame to a simple binary image of edges. The design has been developed in a parallel fashion and with specific architectural solutions so as to allow a fast response without degrading the functional performances. Experimental results on synthetic and real data show that our implementation, synthesized onto a Xilinx Spartan-3A DSP 3400A device, succesfully runs in real-time with a low resource occupation, while maintaining a functionality comparable with the floating-point software version.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.