An efficient Elastic Net method for edge linking of images

Junyan Yi, Gang Yang, Yuki Todo, Zheng Tang
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Abstract

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.
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一种有效的图像边缘连接弹性网方法
边连接是一个基本的计算机视觉问题,可以看作是一个约束优化问题,它是NP困难的,与经典的旅行商问题同构。本文提出了一种有效的图像边缘连接弹性网方法。在弹性网络中引入动态参数策略,使网络具有较强的边缘点搜索能力,更快收敛到最优或近最优解。对一系列人工图像进行了仿真。结果表明,该方法有效地提高了经典弹性网的求解质量和收敛速度。
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