DocumentCode :
2240562
Title :
Robust affine invariant matching with application to line features
Author :
Tsai, Frank C D
Author_Institution :
Courant Inst. of Math. Sci., New York Univ., NY, USA
fYear :
1993
fDate :
15-17 Jun 1993
Firstpage :
393
Lastpage :
399
Abstract :
Line features in geometric hashing are discussed. Lines are used as the primitive features to compute the geometric invariants, combining the Hough transform with a variation of geometric hashing as a technique for model-based object recognition in seriously degraded single intensity images. The effect of uncertainty of line features on the computed invariants for the case where images are formed under affine viewing transformations is analytically determined. The system is implemented with experiments on polygonal objects, which are modeled by lines. It is shown that the technique is noise resistant and suitable in an environment containing many occlusions
Keywords :
Hough transforms; feature extraction; image recognition; image sequences; Hough transform; affine viewing transformations; geometric hashing; geometric invariants; line features; model-based object recognition; noise resistant; polygonal objects; primitive features; robust affine invariant matching; seriously degraded single intensity images; uncertainty; Degradation; Image analysis; Image edge detection; Image segmentation; Layout; Object recognition; Petroleum; Robot sensing systems; Robustness; Solid modeling; Uncertainty; Working environment noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on
Conference_Location :
New York, NY
ISSN :
1063-6919
Print_ISBN :
0-8186-3880-X
Type :
conf
DOI :
10.1109/CVPR.1993.341100
Filename :
341100
Link To Document :
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