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AUTOMATIC TEXT EXTRACTION FROM COMPLEX COLORED IMAGES USING GAMMA CORRECTION METHOD

机译:利用伽玛校正方法从复杂彩色图像中自动提取文本

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The aim of this study is to propose a new methodology for text region extraction and non text region removal from complex background colored images. This study presents a new approach based on Gamma correction by determining a gamma value for enhancing the foreground details in an image. The approach also uses gray level co-occurrence matrices, texture measures, threshold concepts. The proposed method is a useful preprocessing technique to remove non text region and to show the text region in the image. Experiments were on various images from the datasets collected and tagged by the ICDAR robust reading dataset collection team. Experimental results show that the proposed method has a good performance on extracting text regions in an image.
机译:这项研究的目的是提出一种从复杂背景彩色图像中提取文本区域和去除非文本区域的新方法。这项研究通过确定用于增强图像前景细节的伽玛值,提出了一种基于伽玛校正的新方法。该方法还使用灰度共现矩阵,纹理量度和阈值概念。所提出的方法是一种有用的预处理技术,用于去除非文本区域并在图像中显示文本区域。实验是在ICDAR稳健阅读数据集收集团队收集和标记的数据集中的各种图像上进行的。实验结果表明,该方法在提取图像文本区域方面具有良好的性能。

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