Defect Detection in Pipes using a Mobile Laser-Optics Technology and Digital Geometry

This paper presents a novel method for defect detection in pipes using a mobile laser-optics technology and conventional digital-geometry-based image processing techniques. The laser-optics consists of a laser that projects a line onto the pipe’s surface, and an omnidirectional camera. It can be mounted on a pipe crawling robot for conducting continuous inspection. The projected laser line will be seen as a half-oval in the image. When the laser line passes over defected points, the image moments on the pixel information would change. We propose a B-spline curve fitting on the digitally-convoluted image and a curvature estimation algorithm to detect the defects from the image. Defect sizes of 2 mm or larger can be detected using this method in pipes of up to 24 inch in diameter. The proposed sensor can detect 180-degree (i.e., upper half surface of the pipe). By turning the sensor 180 degrees, one will be able to detect the other half (i.e., lower half of the pipe’s surface). While, 360-degree laser rings are available commercially, but they did not provide the intensity needed for our experimentation. We also propose a fast boundary extraction algorithm for real time detection of defects, where a trace of consecutive images are used to track the image features. Tests were carried out on PVC and steel pipes

Defect Detection in Pipes using a Mobile Laser-Optics Technology and Digital Geometry

This paper presents a novel method for defect detection in pipes using a mobile laser-optics technology and conventional digital-geometry-based image processing techniques. The laser-optics consists of a laser that projects a line onto the pipe’s surface, and an omnidirectional camera. It can be mounted on a pipe crawling robot for conducting continuous inspection. The projected laser line will be seen as a half-oval in the image. When the laser line passes over defected points, the image moments on the pixel information would change. We propose a B-spline curve fitting on the digitally-convoluted image and a curvature estimation algorithm to detect the defects from the image. Defect sizes of 2 mm or larger can be detected using this method in pipes of up to 24 inch in diameter. The proposed sensor can detect 180-degree (i.e., upper half surface of the pipe). By turning the sensor 180 degrees, one will be able to detect the other half (i.e., lower half of the pipe’s surface). While, 360-degree laser rings are available commercially, but they did not provide the intensity needed for our experimentation. We also propose a fast boundary extraction algorithm for real time detection of defects, where a trace of consecutive images are used to track the image features. Tests were carried out on PVC and steel pipes

A DISTRIBUTED AGENT MEDIA ACCESS FRAMEWORK

This paper presents a distributed software mobile agent framework for media access. The access and delivery of media is enhanced by an agent architecture framework that utilizesmobile agent characteristics to provide access and delivery of media. Migrating agents to the media source and destination devices enables the framework to discover the properties of devices and media within networks dynamically. The mobile agents in this framework make decisions and work together to enable access and delivery of media through the transcoding of media based on the properties of the data path and device constraints