Deep FCN for Arabic Scene Text Detection

I. Beltaief, Mohamed Ben Halima
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引用次数: 2

Abstract

Visual text is considered as one of the major indispensable aspects of communication field used by individuals and broadly applied in our daily Transactions. Thus, detecting and exploiting this textual information is of a big prominence. State of the art methods for detecting text on printed documents has achieved impressing results on both accuracy and precision values thanks to the sophisticated deep earning approaches, while researchers on natural scenes images still on progress due to the various difficulties on distinguishing text candidates from the remaining shapes. wherefore, as a fast and efficient solution, we propose a deep incorporated multilingual scene text detector system to forthwith localize text using an end-to-end trainable single Network. For training and testing stages, we have used the ACTIV [24] dataset.
用于阿拉伯语场景文本检测的深度FCN
视觉文本被认为是个人使用的交流领域中不可缺少的重要方面之一,在我们的日常生活中得到了广泛的应用。因此,对这些文本信息的检测和开发就显得尤为重要。由于复杂的深度学习方法,用于检测打印文档上的文本的最先进方法在准确性和精度值上都取得了令人印象深刻的结果,而自然场景图像的研究人员仍在进展,因为在从剩余形状中区分文本候选者方面存在各种困难。因此,作为一种快速有效的解决方案,我们提出了一种深度融合的多语言场景文本检测系统,该系统使用端到端可训练的单一网络立即对文本进行本地化。对于训练和测试阶段,我们使用了ACTIV[24]数据集。
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