DocumentCode :
3707373
Title :
Delaunay-supported edges for image graphs
Author :
Nicholas Dahm;Yongsheng Gao;Terry Caelli;Horst Bunke
Author_Institution :
School of Engineering, Griffith University, Brisbane, Australia
fYear :
2015
Firstpage :
1036
Lastpage :
1040
Abstract :
Graphs are a powerful and versatile data structure for pattern recognition. However, their flexibility brings inherent complexities for algorithms which seek to create or utilise graphs. In the context of computer vision, many feature detection algorithms can extract a suitable vertex set from an image. The creation of edges between these vertices presents new challenges, and effective methods for edge creation only exist for certain types of vertices such as points and regions. This paper presents a novel method for creating edges for image graphs, while supporting a wide array of vertex types. The presented method is principled, and its robustness is shown experimentally against a number of affine and projective transforms, as well as noise.
Keywords :
"Image edge detection","Transforms","Feature extraction","Robustness","Computer vision","Topology","Silicon"
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/ICIP.2015.7350957
Filename :
7350957
Link To Document :
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