Edge Detection in Pipe Images Using Classification of Haar Wavelet Transforms

Autor:	Mike Rahilly, Donavan Marney, Brad Lane, John Mashford, Stewart Burn
Rok vydání:	2014
Předmět:	Morphological gradient Pixel Physics::Instrumentation and Detectors Computer science business.industry Detector ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Deriche edge detector Edge detection Haar wavelet Artificial Intelligence Computer Science::Computer Vision and Pattern Recognition Canny edge detector Computer vision Artificial intelligence business Image gradient
Zdroj:	Applied Artificial Intelligence. 28:675-689
ISSN:	1087-6545 0883-9514
DOI:	10.1080/08839514.2014.927689
Popis:	Automatic image interpretation for pipe inspection is a relatively recent area of research, which has great potential benefit. An important component of such systems is crack detection, or, more generally, edge or discontinuity detection. This paper describes a new approach to edge detection and applies it to pipe images. The method labels each pixel in an image as an edge pixel or a nonedge pixel by processing the Haar wavelet transform of the image in a window about the pixel using a support vector machine. As a pixel classifier, to within a moderate morphological tolerance, the detector has an accuracy of 99% on the images on which it has been tested and compares favorably with the commonly used Canny edge detector.
Databáze:	OpenAIRE
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