Design of Low Vision Electronic Glasses with Image Processing Capabilities Using Raspberry Pi

Rachmad Setiawan, Rayhan Akmal Fadlurahman, Nada Fitrieyatul Hikmah
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Abstract

Poor vision is one of the most common eye health issues worldwide. Low vision patients are typically treated with optical devices or by substituting hearing or touch for visual capabilities. Head-mounted displays are currently the most promising form of low-vision assistive technology since they utilize the user's remaining natural visual capabilities. In this work, a prototype head-mounted display-based low-vision tool in the form of electronic glasses was designed utilizing a Raspberry Pi computer. The prototype was created using a Raspberry Pi 4 B coupled with cameras to allow real-time video acquisition. The LCD on the electronic eyewear frame as the camera showed the video recording. The prototype also included software utilizing five image processing modes—magnification, brightness enhancement, adaptive contrast enhancement, edge enhancement, and text detection and recognition- to help persons with limited vision acquire visual information more effectively. OpenCV was used with Python to create the software system. Average framerate measurements of 30–40 FPS for brightness and contrast improvement modes, 20 FPS for zooming and edge enhancement modes, and 1.3 FPS for text identification modes showed that the concept of electronic spectacles was successfully implemented in this research.
利用树莓派设计具有图像处理能力的低视力电子眼镜
视力不佳是世界上最常见的眼部健康问题之一。低视力患者通常使用光学设备或用听觉或触觉代替视觉。头戴式显示器是目前最有前途的低视力辅助技术形式,因为它们利用了用户剩余的自然视觉能力。在这项工作中,利用树莓派计算机设计了一个以电子眼镜形式的基于头戴式显示器的低视力工具原型。原型是使用树莓派4b和摄像头创建的,以便实时视频采集。电子眼镜框上的液晶显示摄像头正在录制视频。该原型还包括利用五种图像处理模式(放大、亮度增强、自适应对比度增强、边缘增强、文本检测和识别)的软件,以帮助视力受限的人更有效地获取视觉信息。OpenCV与Python一起用于创建软件系统。亮度和对比度提升模式的平均帧率为30-40 FPS,变焦和边缘增强模式的平均帧率为20 FPS,文本识别模式的平均帧率为1.3 FPS,表明本研究成功实现了电子眼镜的概念。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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