DocumentCode :
2662827
Title :
Invariance analysis and application of the zoomed-and-shrunk image singular value vector
Author :
Jing, Yuan ; Ying, Yang ; Danqi, Chen ; Hui, Wang
Author_Institution :
Dept. of Disaster Inf. Eng., Inst. of Disaster Prevention Sci. & Technol., Sanhe, China
Volume :
2
fYear :
2010
fDate :
3-5 Oct. 2010
Abstract :
The image singular value vector has been applied extensively to image processing and recognition for its stability and invariance in the transformation of translation,rotation, transposition and mirroration. This paper is to try to analyse how the image singular value vector to change with image size changing by performing matrix operation and experiment; then apply the conclusions to template-matching. Experiments are performed to show that the singular value has robust performance and the strategy based on the singular value is practical and efficient in image processing.
Keywords :
image matching; image recognition; singular value decomposition; vectors; image processing; image recognition; image singular value vector; invariance analysis; matrix operation; mirroration property; rotation property; template matching; translation property; transposition property; zoomed-and-shrunk image; Eigenvalues and eigenfunctions; Equations; Face recognition; Pixel; Singular value decomposition; Software; Watermarking; Singular value decomposition(SVD); image shrinking and zooming; invariance; template-matching;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Technology and Engineering (ICSTE), 2010 2nd International Conference on
Conference_Location :
San Juan, PR
Print_ISBN :
978-1-4244-8667-0
Electronic_ISBN :
978-1-4244-8666-3
Type :
conf
DOI :
10.1109/ICSTE.2010.5608836
Filename :
5608836
Link To Document :
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