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基于自动目标检测算法的盲文图像生成系统,用于识别视障人士生活中的障碍物。

Automatic Object Detection Algorithm-Based Braille Image Generation System for the Recognition of Real-Life Obstacles for Visually Impaired People.

机构信息

IT Convergence Engineering and Computer Convergence Major, Gachon University, Seongnam 13120, Korea.

出版信息

Sensors (Basel). 2022 Feb 18;22(4):1601. doi: 10.3390/s22041601.

Abstract

The global prevalence of visual impairment due to diseases and accidents continues to increase. Visually impaired individuals rely on their auditory and tactile senses to recognize surrounding objects. However, accessible public facilities such as tactile pavements and tactile signs are installed only in limited areas globally, and visually impaired individuals use assistive devices such as canes or guide dogs, which have limitations. In particular, the visually impaired are not equipped to face unexpected situations by themselves while walking. Therefore, these situations are becoming a great threat to the safety of the visually impaired. To solve this problem, this study proposes a living assistance system, which integrates object recognition, object extraction, outline generation, and braille conversion algorithms, that is applicable both indoors and outdoors. The smart glasses guide objects in real photos, and the user can detect the shape of the object through a braille pad. Moreover, we built a database containing 100 objects on the basis of a survey to select objects frequently used by visually impaired people in real life to construct the system. A performance evaluation, consisting of accuracy and usefulness evaluations, was conducted to assess the system. The former involved comparing the tactile image generated on the basis of braille data with the expected tactile image, while the latter confirmed the object extraction accuracy and conversion rate on the basis of the images of real-life situations. As a result, the living assistance system proposed in this study was found to be efficient and useful with an average accuracy of 85% a detection accuracy of 90% and higher, and an average braille conversion time of 6.6 s. Ten visually impaired individuals used the assistance system and were satisfied with its performance. Participants preferred tactile graphics that contained only the outline of the objects, over tactile graphics containing the full texture details.

摘要

全球因疾病和事故导致的视力障碍患病率持续上升。视力障碍者依靠听觉和触觉来识别周围物体。然而,全球仅有有限的区域安装了可供使用的公共设施,如触觉人行道和触觉标志,而视力障碍者使用的辅助设备,如手杖或导盲犬,存在局限性。特别是,视力障碍者在行走时无法独自应对突发情况,因此这些情况对视力障碍者的安全构成了极大威胁。为了解决这个问题,本研究提出了一种室内外均可应用的生活辅助系统,该系统集成了物体识别、物体提取、轮廓生成和盲文转换算法。智能眼镜可引导真实照片中的物体,用户可通过盲文垫检测物体的形状。此外,我们基于一项调查建立了一个包含 100 个物体的数据库,从中选择了生活中视力障碍者常用的物体来构建系统。我们还进行了性能评估,包括准确性和有用性评估,以评估系统。前者涉及比较基于盲文数据生成的触觉图像与预期的触觉图像,后者则根据真实场景的图像确认物体提取的准确性和转换率。结果表明,本研究提出的生活辅助系统具有较高的效率和实用性,平均准确率为 85%,检测准确率为 90%及以上,平均盲文转换时间为 6.6 秒。十位视力障碍者使用了该辅助系统,对其性能表示满意。参与者更喜欢仅包含物体轮廓的触觉图形,而不是包含完整纹理细节的触觉图形。

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