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An Efficient Method of Text Localization in Complicated Background Scenes

机译:复杂背景场景中的文本本地化的高效方法

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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:我们提出了一种新的文本定位方法,在带有复杂的背景场景的低照明图像中的文本定位。低照明图像,复杂背景和文本脚本的变体使文本定位问题具有挑战性。所提出的方法在残余边缘图像中使用基于密度的信息和矩形窗口。所提出的方法首先是从RGB到YCBCR颜色空间的色彩空间转换,其次我们从YCBCR颜色空间提取y分量并从Y分量获取图像增强,然后提取增强型y分量的垂直边缘,第三,长曲线和随机噪声在复杂的背景中被删除,最后,搜索文本本地化并从原始低照明图像分段出文本。我们使用自然图像数据集和ICDAR数据集评估我们的方法。实验结果表明,与其他方法相比,该方法对干扰特性更加强大,更准确。

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