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
fDate :
3/1/1999 12:00:00 AM
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;
Journal_Title :
Image Processing, IEEE Transactions on
