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 :
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