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Assistive Text Reading from Complex Background for Blind Persons

机译:复杂背景下的盲人辅助文本阅读

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In the paper, we propose a camera-based assistive system for visually impaired or blind persons to read text from signage and objects that are held in the hand. The system is able to read text from complex backgrounds and then communicate this information aurally. To localize text regions in images with complex backgrounds, we design a novel text localization algorithm by learning gradient features of stroke orientations and distributions of edge pixels in an Adaboost model. Text characters in the localized regions are recognized by off-the-shelf optical character recognition (OCR) software and transformed into speech outputs. The performance of the proposed system is evaluated on ICDAR 2003 Robust Reading Dataset. Experimental results demonstrate that our algorithm outperforms previous algorithms on some measures. Our prototype system was further evaluated on a dataset collected by 10 blind persons, with the system effectively reading text from complex backgrounds.
机译:在本文中,我们提出了一种基于摄像头的辅助系统,该系统可用于视力障碍或盲人从标牌和手持物体读取文本。该系统能够从复杂的背景中读取文本,然后通过听觉方式传达此信息。为了在具有复杂背景的图像中定位文本区域,我们通过学习Adaboost模型中笔触方向的梯度特征和边缘像素的分布来设计一种新颖的文本定位算法。本地区域中的文本字符可以通过现成的光学字符识别(OCR)软件进行识别,并转换为语音输出。建议的系统的性能在ICDAR 2003稳健读取数据集上进行了评估。实验结果表明,我们的算法在某些方面优于以前的算法。我们的原型系统在由10个盲人收集的数据集上进行了进一步评估,该系统可有效读取复杂背景下的文本。

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