High-Speed, High-Resolution 3-D Machine Vision for Automated Inspection of Highway Pavement Surfaces

用于自动检测公路路面的高速、高分辨率 3D 机器视觉

• 批准号: 9900337
• 负责人: Peisen Huang
• 金额: $ 23.23万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-08-15 至 2004-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9900337&HistoricalAwards=false
• 关键词: Speed; Resolution; Machine; Vision; Automated

The highway system is vital to the economy of the United States. According to the survey conducted by the Federal Highway Administration, 90 percent of personal travel and 25 percent of freight movement is served by highways. In 1998, federal, state, and local governments are expected to spend a combined sum of over $106 billion on highways. A significant portion of it will be used for system preservation, in particular, pavement 3R (reconstruction, rehabilitation, and resurface). Inspection of pavement surface conditions plays a pivotal role in pavement 3R. Currently, these inspections are dome mostly by manual visual inspection. This is a slow, labor-intensive, tedious, dangerous, expensive, and subjective method. To solve these problems, an automated inspection system needs to be developed. In this research, we propose to develop a novel 3-D machine vision technique for automated inspection of pavement surfaces. This technique is based on a color-encoded fringe projection and phase shifting concept that provides high-speed (limited only by the frame rate of the camera) and high-resolution (limited only by the number of pixels in the camera) 3-D surface contouring capability. Integrated with a specially developed vehicle, the system can provide real-time inspections of pavement surface conditions at normal highway speeds (55 mph). With advanced algorithms developed based on wavelet analysis, automatic detection, identification, and measurment of various types of pavement distresses can be realized. Moreover, if global positioning system (GPS) and a map software are used, it is possible to pinpoint the locations of pavement distresses and if necessary, lead the repair engineerrs of workers to the sites. The objectives of the proposed research are as follows: 1. Develop a novel 3-D machine vision technique based on color-encoded fringe projection and phase shifting for high-speed, high-resolution pavement inspection. 2. Develop a special vehicle that incorporates the 3-D machine vision system and GP5 for automated pavement data collection at highway speeds. 3. Develop algorithms for sutomatic detection and quantitative evalutation of pavement surface distresses based on wavelet analysis techniques.

高速公路系统对美国经济至关重要。 根据联邦公路管理局进行的调查，90%的个人旅行和25%的货物运输是由公路提供服务的。 1998年，预计联邦、州和地方政府在公路上的总支出将超过1060亿美元。 其中很大一部分将用于系统保护，特别是路面3R（重建、修复和重铺）。 路面状况的检测在路面3R中起着至关重要的作用。 目前，这些检查大多是通过人工目视检查。 这是一种缓慢、劳动密集、乏味、危险、昂贵且主观的方法。 为了解决这些问题，需要开发自动化检测系统。 在这项研究中，我们建议开发一种新的3-D机器视觉技术的自动检测路面。 该技术基于彩色编码条纹投影和相移概念，其提供高速（仅受相机的帧速率限制）和高分辨率（仅受相机中的像素数量限制）3D表面轮廓绘制能力。 该系统与专门开发的车辆相结合，可以在正常公路速度（55英里/小时）下提供路面状况的实时检查。 基于小波分析的先进算法，可以实现各种路面病害的自动检测、识别和测量。 此外，如果使用全球定位系统（GPS）和地图软件，则可以精确定位路面损坏的位置，并在必要时将维修工程师或工人带到现场。 本文的研究目标如下：1. 开发一种基于彩色编码条纹投影和相移的新型三维机器视觉技术，用于高速、高分辨率路面检测。 2. 开发一种特殊的车辆，它结合了3-D机器视觉系统和GP 5，用于在高速公路上自动收集路面数据。 3. 提出了基于小波分析技术的路面病害监测与定量评价算法。