DocumentCode
811232
Title
Similarity and affine invariant distances between 2D point sets
Author
Werman, Michael ; Weinshall, Daphna
Author_Institution
Dept. of Comput. Sci., Hebrew Univ., Jerusalem, Israel
Volume
17
Issue
8
fYear
1995
fDate
8/1/1995 12:00:00 AM
Firstpage
810
Lastpage
814
Abstract
We develop expressions for measuring the distance between 2D point sets, which are invariant to either 2D affine transformations or 2D similarity transformations of the sets, and assuming a known correspondence between the point sets. We discuss the image normalization to be applied to the images before their comparison so that the computed distance is symmetric with respect to the two images. We then give a general (metric) definition of the distance between images, which leads to the same expressions for the similarity and affine cases. This definition avoids ad hoc decisions about normalization. Moreover, it makes it possible to compute the distance between images under different conditions, including cases where the images are treated asymmetrically. We demonstrate these results with real and simulated images
Keywords
image matching; 2D affine transformations; 2D point sets; 2D similarity transformations; affine invariant distances; image normalization; metric; similarity distances; Cameras; Computational modeling; Computer science; Covariance matrix; Euclidean distance; Pattern analysis; Pattern matching;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.400572
Filename
400572
Link To Document