Object matching algorithms using robust Hausdorff distance measures
- 1 March 1999
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Image Processing
- Vol. 8 (3), 425-429
- https://doi.org/10.1109/83.748897
Abstract
A Hausdorff distance (HD) is one of commonly used measures for object matching. This work analyzes the conventional HD measures and proposes two robust HD measures based on m-estimation and least trimmed square (LTS) which are more efficient than the conventional HD measures. By computer simulation, the matching performance of the conventional and proposed HD measures is compared with synthetic and real images.Keywords
This publication has 17 references indexed in Scilit:
- Robust Window OperatorsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Navigation parameter estimation from sequential aerial imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- A new robust operator for computer vision: theoretical analysisPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1994
- Robust regression methods for computer vision: A reviewInternational Journal of Computer Vision, 1991
- Nonlinear Digital FiltersPublished by Springer Nature ,1990
- VLSI median filtersIEEE Transactions on Acoustics, Speech, and Signal Processing, 1990
- Hierarchical chamfer matching: a parametric edge matching algorithmIEEE Transactions on Pattern Analysis and Machine Intelligence, 1988
- Robust Regression and Outlier DetectionWiley Series in Probability and Statistics, 1987
- Software and VLSI algorithms for generalized ranked order filteringIEEE Transactions on Circuits and Systems, 1987
- Shape Matching of Two-Dimensional ObjectsIEEE Transactions on Pattern Analysis and Machine Intelligence, 1984