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Automatic Categorization of Image Regions Using Dominant Color Based Vector Quantization

机译:基于主基的矢量量化自动分类图像区域

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This paper proposes a dominant color based vector quantization algorithm that automatically categorizes image regions. In contrast to the conventional vector quantization algorithm, the new algorithm effectively handles variable feature vectors like dominant color descriptors. Furthermore, the algorithm is guided by a novel splitting and stopping criterion which is specially designed for dominant color descriptors. This criterion helps the algorithm not only to learn the number of clusters, but also to avoid unnecessary over-fragmentations of region-clusters. Experimental result shows that the proposed approach categorizes image-regions with very high accuracy.
机译:本文提出了一种主导的基于颜色的矢量量化算法,其自动对图像区域进行分类。与传统的向量量化算法相比,新算法有效地处理了定型颜色描述符等变量特征向量。此外,该算法由一种新颖的分割和停止标准引导,其专门设计用于主导颜色描述符。该标准不仅可以了解群集的群集,而且还可以避免区域簇的不必要过碎片。实验结果表明,所提出的方法以非常高的精度分类图像区域。

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