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33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)
Image Primitive Signatures
Cosmos Club, Washington, DC
October 13-October 15
ISBN: 0-7695-2250-5
ASCII Text
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Jason M. Kinser, "Image Primitive Signatures," Applied Image Pattern Recognition Workshop,, pp. 51-54, 33rd Applied Imagery Pattern Recognition Workshop (AIPR'04), 2004.
 
 
BibTex
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@article{ 10.1109/AIPR.2004.28,
author = {Jason M. Kinser},
title = {Image Primitive Signatures},
journal ={Applied Image Pattern Recognition Workshop,},
volume = {0},
year = {2004},
issn = {1550-5219},
pages = {51-54},
doi = {http://doi.ieeecomputersociety.org/10.1109/AIPR.2004.28},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Applied Image Pattern Recognition Workshop,
TI - Image Primitive Signatures
SN - 1550-5219
SP51
EP54
A1 - Jason M. Kinser,
PY - 2004
KW - null
VL - 0
JA - Applied Image Pattern Recognition Workshop,
ER -
 
Jason M. Kinser, George Mason University
Image signatures are generated from the comparison of segments contained within an image to a database of segments collected over a large variety of images. It is impossible to retain all of the segments from all of the images so the segments are clustered becomes an image primitive as each cluster contains a unique set of similar segments. The size of the image signature is NK where N is the number of segments and K is the number of clusters. These numbers are significantly smaller than the dimensions of the image and so a signature is a condensed representation of the contents of the image.
Citation:
Jason M. Kinser, "Image Primitive Signatures," aipr, pp.51-54, 33rd Applied Imagery Pattern Recognition Workshop (AIPR'04), 2004
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