利用灰度模型改进主动形状模型搜索

Tim Cootes, C. Taylor
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引用次数: 54

摘要

我们描述了使用灵活模型来定位图像中的结构的方法。我们之前已经描述了可用于此目的的形状和形状可变性的统计模型(活动形状模型)。在本文中,我们展示了如何将灰度级外观的统计模型结合起来,从而提高可靠性和准确性。我们描述的实验旨在:1)测试活动形状模型在新图像中定位物体的能力;2)评估不同模型参数对性能的影响;3)将使用灰度模型的结果与使用搜索最强边缘的结果进行比较。结果表明,灰阶模型的加入比以前的方案有很大的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using grey-level models to improve active shape model search
We describe methods for using flexible models to locate structures in images. We have previously described statistical models of shape and shape variability which can be used for this purpose (active shape models). In this paper we show how statistical models of grey-level appearance can be incorporated, leading to improved reliability and accuracy. We describe experiments designed to: 1) test how well an active shape model can locate an object in a new image; 2) to assess the effects on performance of varying the model parameters; and 3) to compare the results using grey-level models with those using a search for strongest edges. The results demonstrate that the addition of grey-level models leads to considerable improvement over earlier schemes.
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