Contour-based shape representation using principal curves

Extraction and representation of contours are challenging problems and are crucial for many image processing applications. In this study, given a membership function that returns the score of a point belonging to a contour, we propose a method for contour representation based on the principal curve...

Full description

Saved in:
Bibliographic Details
Published in:Pattern recognition 2013-04, Vol.46 (4), p.1140-1150
Main Authors: Ataer-Cansizoglu, Esra, Bas, Erhan, Kalpathy-Cramer, Jayashree, Sharp, Greg C., Erdogmus, Deniz
Format: Article
Language:English
Subjects:
Applied sciences
Boundary representation
Contours
Curve/contour matching
Exact sciences and technology
Image processing
Information, signal and communications theory
Pattern recognition
Polycarbonates
Representations
Shape
Shape representation and analysis
Signal and communications theory
Signal processing
Signal representation. Spectral analysis
Signal, noise
Telecommunications and information theory
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Extraction and representation of contours are challenging problems and are crucial for many image processing applications. In this study, given a membership function that returns the score of a point belonging to a contour, we propose a method for contour representation based on the principal curve (PC) of this function. The proposed method provides a piecewise linear representation of the contour with fewer points while preserving shape. Varied experiments are conducted, including lung boundary representation in CT images and shape representation in handwritten images. The results show that the technique provides accurate shape representation. ► We extract the contour given a membership function describing the shape. ► Contour points are down-sampled creating a piecewise linear representation. ► Proposed representation is used for images in different domains. ► The experiments show that the technique is insensitive to image noise. ► The technique preserves shape to a user-defined accuracy.
ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2012.10.014