An Efficient Elastic Net Method for Edge linking of Images

Edge linking is a fundamental computer-vision task, viewed as a constrained optimization problem, it is NP hard-being isomorphic to the classical traveling salesman problem. In this paper, we propose an efficient Elastic Net method for edge linking of images. A dynamic parameter strategy is introduced into the Elastic Net, which enable the network to have superior search ability for edge points and converge sooner to optimal or near-optimal solutions. Simulations are conducted on a series of artificial images. The results confirm that this method effectively improves both the solution quality and convergence speed of the classical Elastic Net.