Quadrangle Detection Based on A Robust Line Tracker Using Multiple Kalman Models
Hung Kwun Fung, Kin Hong Wong · Journal of ICT Research and Applications · 2013
Quadrangle and line tracking are essential for many real world applications of computer vision.In this paper, we propose a computationally efficient line tracker that can robustly and accurately track lines in an image.We use a multiple-model tracking accurately and r filters in parallel.Each filter is configured to use a different state transition model.All the filters are updated by the measurement at the same time following the conventional Kalman combination of outputs from all the Kalman detected, we developed a scheme to merge the lines together to become suitable quadrangles.The experimental result shows that the proposed system can lines and quadrangle robustly in real time.The result is useful in shape detection and should be suitable for building many mobile projector applications.