Scene text detection with gradient guidance

Siyu Chen, Enqi Zhan, Manjie Zhang
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Abstract

In the process of text detection, we frequently encounter numerous indistinct images, which can easily result in text omission and misdetection. Inspired by the SPSR model, we introduce gradient branching to guide the training of text detection models in order to address this problem. By preserving more image edge features, we expect to improve the text detection performance of fuzzy images and fuzzy regions. The experiment demonstrates that the gradient guidance-based text detection model can detect text in ambiguous images more accurately and reduce instances of missing and incorrect detection.
场景文本检测与梯度引导
在文本检测过程中,我们经常会遇到大量模糊的图像,这很容易导致文本遗漏和误检。受SPSR模型的启发,我们引入梯度分支来指导文本检测模型的训练,以解决这一问题。通过保留更多的图像边缘特征,我们期望提高模糊图像和模糊区域的文本检测性能。实验表明,基于梯度引导的文本检测模型可以更准确地检测出模糊图像中的文本,减少了检测缺失和错误的情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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