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Scene Text Extraction in IHLS Color Space Using Support Vector Machine

机译:支持向量机在IHLS颜色空间中场景文本提取。

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摘要

Scene text extraction is challenging research area due to variety of image degradations caused by imaging conditions and low cost consumer devices. In this paper we propose text extraction method that uses chroma and lightness component for generation of extraction hypotheses and incorporates SVM (support vector machine) based text detection stage as tool for hypotheses verification. Choice of chroma and lightness components is based on their complementarity with respect to image degradations like shadows and highlights. Another novelty is usage of IHLS color space for text extraction task which is motivated by saturation definition that eliminates instability of this component at low lightness values. Results obtained on the ICDAR 2011 dataset confirm complementarity of chroma and lightness. Compared to the state-of-the-art methods proposed algorithm achieves higher correct recognition rate and comparable total edit distance. DOI: http://dx.doi.org/10.5755/j01.itc.44.1.5757
机译:由于成像条件和低成本消费类设备导致的各种图像质量下降,场景文本提取成为具有挑战性的研究领域。在本文中,我们提出了一种文本提取方法,该方法使用色度和明度分量生成提取假设,并将基于SVM(支持向量机)的文本检测阶段作为假设验证的工具。色度和亮度成分的选择是基于它们与图像质量(例如阴影和高光)的互补性。另一个新颖之处是将IHLS颜色空间用于文本提取任务,这是由饱和度定义驱动的,该饱和度定义消除了该组件在低亮度值下的不稳定性。从ICDAR 2011数据集获得的结果证实了色度和亮度的互补性。与最新技术相比,该算法可实现更高的正确识别率和可比的总编辑距离。 DOI:http://dx.doi.org/10.5755/j01.itc.44.1.5757

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