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Adaptive spatio-colorimetric classification

机译:自适应时空比色分类

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摘要

Unlike most color classification methods, which consist in partitioning the image according to the pixels color attributes exclusively, spatio-colorimetric techniques bring some spatial information directly among the data to classify. However, they usually involve some heavy data structures and a large amount of trichromatic data.rnTo answer this issue, this article proposes a color spatio-classification method performing two successive stages. First of all, the number of colors is lowered through an analysis of the connectedness degrees on the three marginal components independently. Since the number of colors is significantly reduced, it becomes reasonable, in a complexity point of view, to analyze the vectorial connectedness degrees of the trichromatic intervals. Several experimental results will be shown on different images and the method parameters will be discussed.
机译:与大多数颜色分类方法不同,时空比色技术不同于仅根据像素颜色属性对图像进行分区的方法,而空间比色技术则将一些空间信息直接带入数据中进行分类。但是,它们通常涉及一些繁重的数据结构和大量的三色数据。为了解决这个问题,本文提出了一种进行两个连续阶段的颜色空间分类方法。首先,通过对三个边缘分量的连接度进行独立分析,减少了颜色数量。由于显着减少了颜色的数量,因此从复杂性的角度来看,分析三色间隔的矢量连接度变得合理。几个实验结果将显示在不同的图像上,并将讨论方法参数。

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