基于深度学习的盲人行路辅助软件设计

Design of Walking Assistance Software for Blind People Based on Deep Learning

随着时代的进步,科技化的社会给部分人的生活带来了极大便利,但也使视障人群的生活变得举步维艰,针对国内关于盲人导盲设备的设计存在的不足,如智能化低、精度不高、无法对障碍物进行实时警报等,本文提出了一种结合计算机视觉和自然语言处理的盲人辅助行路的软件设计方案,利用视频检测技术实现实时检测过往车辆、行人以及障碍物,分析其所处位置,并对检测出的目标进行话术丰富,再基于语音合成技术将检测到的周围目标进行实时播报,为盲人提供相应的语音辅助指导,测试结果表明,上述系统能够以低成本的方法实现提高实用性、保障用户安全并且增加测障精度,使得盲人出行与生活更加方便。

With the progress of the times, the technological society has brought great convenience to the lives of some people, but it has also made the lives of visually impaired people difficult. Due to low intelligence, low precision, and inability to provide real-time alerts to obstacles, this paper proposes a software design scheme for blind people’s assisted walking that combines computer vision and natural language processing. Video detection technology is used to detect passing vehicles, pedestrians and obstacles, analyze their locations, enrich the detected targets, and then broadcast the detected surrounding targets in real time based on speech synthesis technology, providing corresponding voice assistance guidance for the blind. The test results show that the above system can be implemented in a low-cost way to improve the practicability, ensure the safety of users, and in-crease the accuracy of obstacle detection, making travel and life of the blind more convenient.