DocumentCode
3074314
Title
Automated Assessment Tool for the Depth of Pipe Deterioration
Author
Swarnalatha, P. ; Kota, Madhuri ; Resu, Nagarjuna Reddy ; Srivasanth, G.
Author_Institution
Sch. of Comput. Sci., VIT Univ., Vellore
fYear
2009
fDate
6-7 March 2009
Firstpage
721
Lastpage
724
Abstract
Defects in underground pipeline images are indicative of the condition of buried infrastructures like sewers and water mains. This paper entitled automated assessment Tool for the depth of pipe deterioration presents a three step method which is a simple, robust and efficient one to detect defects in the underground concrete pipes. It identifies and extracts defect-like structures from pipe images whose contrast has been enhanced. We propose to use segmentation and feature extraction using structural elements. The main objective behind using this tool is to find the dimensions of the defect such as the length, width and depth and also the type of defect. The detection of defects in buried pipes is a crucial step in assessing the degree of pipe deterioration for municipal operators. Although the human eye is extremely effective at recognition and classification, it is not suitable for assessing pipe defects in thousands of miles of pipeline because of fatigue, subjectivity and cost. Our objective is to reduce the effort and the labour of a person in detecting the defects in underground pipes.
Keywords
feature extraction; image classification; image segmentation; object detection; pipelines; automated assessment tool; defect-like structure extraction; feature extraction; pipe deterioration; underground concrete pipes; underground pipeline images; Costs; Fatigue; Feature extraction; Histograms; Humans; Image analysis; Image enhancement; Image recognition; Image segmentation; Pipelines; Contrast Stretching; Feature Extraction; Histogram Equalization; Image Enhancement; Image Segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Advance Computing Conference, 2009. IACC 2009. IEEE International
Conference_Location
Patiala
Print_ISBN
978-1-4244-2927-1
Electronic_ISBN
978-1-4244-2928-8
Type
conf
DOI
10.1109/IADCC.2009.4809101
Filename
4809101
Link To Document