DocumentCode
1131704
Title
Automatic Threshold Setting for the Sequential Similarity Detection Algorithm
Author
Onoe, Morio ; Saito, Masaru
Author_Institution
Institute of Industrial Science, University of Tokyo
Issue
10
fYear
1976
Firstpage
1052
Lastpage
1053
Abstract
This correspondence presents a method for automatic setting of both constant and increasing thresholds to be used with the sequential similarity detection algorithm (SSDA) for a fast registration of digitized images. No a priori knowledge of image statistics is required. The usefulness of the method is proven in the cloud tracking.
Keywords
Automatic threshold setting, cloud tracking, digital image registration, fast algorithm for registration, feature detection, pattern recognition, sequential similarity detection algorithm, translational image registration, weather satellite.; Artificial satellites; Clouds; Computer vision; Detection algorithms; Digital images; Image registration; Noise level; Pattern recognition; Random variables; Statistics; Automatic threshold setting, cloud tracking, digital image registration, fast algorithm for registration, feature detection, pattern recognition, sequential similarity detection algorithm, translational image registration, weather satellite.;
fLanguage
English
Journal_Title
Computers, IEEE Transactions on
Publisher
ieee
ISSN
0018-9340
Type
jour
DOI
10.1109/TC.1976.1674547
Filename
1674547
Link To Document