DocumentCode
1742362
Title
Robust detection of skewed symmetries
Author
Shen, Dinggang ; Ip, Heorace H S ; Teoh, Eam Khwang
Author_Institution
Dept. of Radiol., Johns Hopkins Univ., MD, USA
Volume
3
fYear
2000
fDate
2000
Firstpage
1010
Abstract
An affine-invariant feature vector, which captures local and semi-local features, has been used in the detection of skewed symmetries. Here, the problem of symmetry axes detection has been formulated as a line detection problem, with known orientations within a local similarity matrix computed for a shape. Moreover, our technique allows all the local reflection-symmetries within an object to be detected. Experiments on detecting skewed symmetries of self-symmetric objects and generalized objects, under noise and occlusions, have demonstrated the effectiveness of this method
Keywords
feature extraction; matrix algebra; symmetry; line detection problem; local similarity matrix; occlusions; robust detection; self-symmetric objects; skewed symmetries; symmetry axes detection; Computer science; Computer vision; Feature extraction; Noise shaping; Object detection; Radiology; Robustness; Sampling methods; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location
Barcelona
ISSN
1051-4651
Print_ISBN
0-7695-0750-6
Type
conf
DOI
10.1109/ICPR.2000.903716
Filename
903716
Link To Document