快速活动轮廓采样

J. Hernandez, F. Prieto, T. Redarce
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引用次数: 8

摘要

本文提出了一种新的用于图像解释中快速提取的活动轮廓模型,称为快速活动轮廓采样(FACS)。所描述的过程是基于在能量最小化阶段使用采样窗口。由于计算最小化过程与经典的活动轮廓最小化过程之间的独立性,该方法可以与大多数其他活动轮廓方法相结合。实验结果表明,与其他类似的快速活动轮廓模型相比,该模型只需很少的迭代就能快速收敛到目标边界,并且在减少计算时间方面有所改善
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Fast Active Contours for Sampling
This paper presents a novel implementation of active contour model for fast extraction in image interpretation called fast active contours for sampling (FACS). The described process is based on the use of a sampling window in the phase of minimization of the energy. The method can be combined with most of the other active contour approaches presented, thanks to the independence between the computational minimization process and the classical active contour minimization process. Experimental result is a fast active contour convergence towards desired object boundaries and its show improvements in terms of computational time reduction after only very few iterations, when compared with other similar fast active contour models
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