DocumentCode :
1720445
Title :
An Approach Using Mathematical Morphology and Support Vector Machines to Detect Features in Pipe Images
Author :
Mashford, John ; Rahilly, Mike ; Davis, Paul
Author_Institution :
Commonwealth Sci. & Ind. Res. Organ., Highett, VIC
fYear :
2008
Firstpage :
84
Lastpage :
89
Abstract :
This paper presents a new approach to detecting features in pipe images based on a generalisation of the erosion operation. The pipe images can be segmented using support vector machine or other method. The binary image obtained in this way contains a principal connected component made up from the pipe flow lines, the pipe joints and adjoining defects. The morphological analysis allows the principal component of the segmented image to be decomposed into its components. Generalisations of the dilation and erosion operations called alpha-dilation and alpha-erosion are defined. Some simple properties of these operations are derived.
Keywords :
image segmentation; mathematical morphology; object detection; alpha-dilation; alpha-erosion; binary image; erosion operation; feature detection; image segmentation; mathematical morphology; morphological analysis; pipe flow lines; pipe images; support vector machines; Brightness; Color; Computer vision; Concrete; Corrosion; Digital images; Image segmentation; Inspection; Morphology; Support vector machines; automatic pipe inspection; mathematical morphology; segmentation; support vector machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Image Computing: Techniques and Applications (DICTA), 2008
Conference_Location :
Canberra, ACT
Print_ISBN :
978-0-7695-3456-5
Type :
conf
DOI :
10.1109/DICTA.2008.25
Filename :
4700004
Link To Document :
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