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 :
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