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An Efficient Method of Text Localization in Complicated Background Scenes

机译:复杂背景场景中文本定位的有效方法

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摘要

We propose a novel method for text localization in low illumination images with complicated background scenes. Low illumination image, complex background and variations of text script make text localization problem challenging. The proposed method use density-based information and rectangle window in the residual edge image. The proposed method firstly is color space conversion from RGB to Ycbcr color space, secondly we extract Y component from Ycbcr color space and get image enhancement from Y component, then extract out the vertical edges of enhanced Y component, thirdly, long curve and random noise in complicated background are removed, finally, search the text localization and segment the text out from the original low illumination images. We evaluate our method using natural image data set and ICDAR data set The experimental results show that the proposed method has more robust to interference characters and more accurate when compared with other methods.
机译:我们提出了一种在背景复杂的低照度图像中进行文本定位的新方法。低照度图像,复杂的背景和文本脚本的变化使文本本地化问题具有挑战性。所提出的方法在残留边缘图像中使用基于密度的信息和矩形窗口。该方法首先是将色彩空间从RGB转换为Ycbcr色彩空间,其次从Ycbcr色彩空间中提取Y分量并从Y分量中得到图像增强,然后提取出增强后的Y分量的垂直边缘,其次是长曲线和随机噪声去除复杂背景中的文本,最后从原始低照度图像中搜索文本位置并将文本分割出来。我们使用自然图像数据集和ICDAR数据集对我们的方法进行了评估。实验结果表明,与其他方法相比,该方法具有更强的抗干扰性和准确性。

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