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A New Approach for Color Character Extraction based on Parallel Clustering

机译:基于并行聚类的彩色字符提取方法

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A new approach of fast color character extraction was proposed. Clustering algorithm was adopted in our method to differentiate between objective character regions and background regions on the premise that character regions are nearly monochromatic. However, the key point of this approach was how to select suitable elements' features based upon the original image information and character's information; it directly determined extraction results. We brought forward a means for feature selection to resolve clustering's key problem, and proved the means is effective. Furthermore, in order to overcome the non-ignorable computational overhead of clustering, parallel clustering algorithm was designed and realized by CUDA. Experiments illustrated color character could be extracted satisfactorily even if these characters are surrounded by complex background; meanwhile, parallel improved method that executed by assist of GPU was more efficient than former method that executed by CPU only.
机译:提出了一种快速彩色字符提取的新方法。在我们的方法中采用聚类算法,以区分目标性质区域和背景区域,在字符区域几乎单色的前提下。但是,这种方法的关键点是如何根据原始图像信息和字符的信息选择合适的元素的特征;它直接确定提取结果。我们提出了一种用于解决群集的关键问题的特征选择的手段,并证明了手段是有效的。此外,为了克服聚类的非忽略计算开销,通过CUDA设计并实现了并行聚类算法。实验说明的颜色角色即使这些字符被复杂的背景包围,也可以令人满意地提取;同时,由GPU的辅助执行的并行改进方法比仅由CPU执行的前方法更有效。

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