场景文本检测的最新解决方案概述

Mladen Džida, Davorin Vukadin, M. Šilić, G. Delač, Klemo Vladimir
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引用次数: 0

摘要

场景文本检测是一种在复杂背景下识别文本区域并用边界框对其进行标记的任务。由于计算机视觉领域深度学习的进步,以及计算机硬件的快速发展,能够处理复杂的神经网络,这一问题近年来受到了广泛的关注,并远非无法解决。使这项任务变得困难的一些最常见的挑战是不规则的文本形状、文本干扰、非常复杂的背景、不同的文本大小和低图像质量。本文概述了最先进的场景文本检测解决方案,其中ICDAR 2015被用作基准数据集。我们比较解决方案的精度,召回率和f分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Overview of State-of-the-art Solutions for Scene Text Detection
Scene text detection is a task of identifying text regions and labeling them with bounding boxes in a complex background. It has received a lot of attention recently and has become far from unsolvable due to progress of deep learning for computer vision and also due to rapid development of computer hardware which is able to process complex neural networks. Some of the most common challenges that make this task difficult are irregular text shapes, text interferences, very complex background, different text sizes and low image quality. This paper presents an overview of state-of-the-art solutions for scene text detection where ICDAR 2015 was used as a benchmark dataset. We compare solutions with respect to precision, recall and F-score.
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