自然场景中垂直文本识别的深度学习框架

Yi Ling Ong, B. Lau, Almon Chai, Christopher McCarthy
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引用次数: 3

摘要

文本检测和识别自然场景图像中的各种文本方向对于理解周围环境具有重要意义。人们对水平文本、定向文本、弯曲文本和垂直文本的检测进行了各种各样的研究。然而,在垂直场景文本检测与识别方面的研究还很有限。垂直场景文本可分为自上而下的垂直文本、自下而上的垂直文本和水平堆叠的垂直文本。除了检测水平文本和方向文本外,本研究提出的模型还可以检测所有类型的垂直场景文本。提出了一种混合垂直场景文本识别的建模方法。该模型包含用于检测场景图像文本区域的多方向文本检测器(Multidirectional Text Detector, MTD),用于识别文本区域文本的二维解码器(Two-dimensional Decoder, 2DD),以及用于确定垂直文本类型的垂直方向网络(Vertical Oriented Network, VON)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Deep Learning Framework for Recognizing Vertical Texts in Natural Scene
Text detection and recognition of various text orientation in natural scene images is important to understand the surrounding. Various research has been carried out on detecting horizontal text, oriented text, curved text and vertical text. However, there are limited research carried out on detecting and recognizing vertical scene text. Vertical scene text can be differentiated into top-to-bottom vertical text, bottom-to-top vertical text and horizontal-stacked vertical text. Apart from detecting horizontal text and oriented text, the model proposed in this research detects all types of vertical scene text. In this paper, the modelling of a hybrid vertical scene texts recognition is proposed. The model contains Multidirectional Text Detector (MTD) for detecting text region in the scene image, Two-dimensional Decoder (2DD) for recognizing texts in the text region, while Vertical Oriented Network (VON) is applied to determine the types of vertical texts.
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