GRoM — Generalized robust multichannel featur detector
GRoM — Generalized robust multichannel featur detector
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GRoM — 广义鲁棒多通道特征检测器
DOI：
10.1109/icsipa.2011.6144155
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
S. Srinivasan
中科院分区：
文献类型：
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作者：
P. Smirnov;P. Semenov;M. Lyakh;A. Chun;Dmitry Gusev;Alexander Redkin;S. Srinivasan
许多著名的图像特征检测计算机视觉算法仅使用亮度或某些特定的颜色模型。虽然这些方法在许多情况下是有效的，但可以表明，由于方法的限制，这些对完整图像信息的转换降低了检测性能。在本文中，我们描述了一种形式化的方法来构建任意数量的通道（无论数据性质如何）的多通道兴趣点检测器，从而最大限度地利用来自这些附加通道的信息。我们介绍了基于该方法的广义鲁棒多通道（GRoM）特征检测器原型，详细介绍了GRoM的特征，并包括一组说明性示例，以突出其与现有方法的区别。
A number of well-known computer vision algorithms for image feature detection use luminosity only or some specific color model. Although these methods are effective in many cases, it can be shown that these transformations of the full image information reduce detection performance due to method-induced restrictions. In this paper, we describe a formal approach to the construction of a multi-channel interest point detector for an arbitrary number of channels (regardless of data nature), which maximizes the benefits from the usage of information from these additional channels. We introduce the Generalized Robust Multi-channel (GRoM) feature detector prototype that is based upon the proposed approach, detail features of GRoM and include a set of illustrative examples to highlight its differentiation from existing methods.