DocumentCode
1478295
Title
Object matching algorithms using robust Hausdorff distance measures
Author
Sim, Dong-Gyu ; Kwon, Oh-Kyu ; Park, Rae-Hong
Author_Institution
Dept. of Electron. Eng., Sogang Univ., Seoul, South Korea
Volume
8
Issue
3
fYear
1999
fDate
3/1/1999 12:00:00 AM
Firstpage
425
Lastpage
429
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
estimation theory; image matching; least squares approximations; least trimmed square; m-estimation; matching performance; object matching algorithms; real images; robust Hausdorff distance measures; synthetic images; Computer simulation; Computer vision; Euclidean distance; High definition video; Image analysis; Object recognition; Robustness; Size measurement; Statistics; Two dimensional displays;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/83.748897
Filename
748897
Link To Document