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Logical/Linear Operators for Image Curves
October 1995 (vol. 17 no. 10)
pp. 982-996
ASCII Text
x 
 
Lee A. Iverson, Steven W. Zucker, "Logical/Linear Operators for Image Curves," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 17, no. 10, pp. 982-996, October, 1995.
 
 
BibTex
x
 
@article{ 10.1109/34.464562,
author = {Lee A. Iverson and Steven W. Zucker},
title = {Logical/Linear Operators for Image Curves},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {17},
number = {10},
issn = {0162-8828},
year = {1995},
pages = {982-996},
doi = {http://doi.ieeecomputersociety.org/10.1109/34.464562},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Logical/Linear Operators for Image Curves
IS - 10
SN - 0162-8828
SP982
EP996
EPD - 982-996
A1 - Lee A. Iverson,
A1 - Steven W. Zucker,
PY - 1995
KW - Edge detection
KW - feature extraction
KW - image processing
KW - computer vision
KW - nonlinear operators.
VL - 17
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 

Abstract—We propose a language for designing image measurement operators suitable for early vision. We refer to them as logical/linear (L/L) operators, since they unify aspects of linear operator theory and Boolean logic. A family of these operators appropriate for measuring the low-order differential structure of image curves is developed. These L/L operators are derived by decomposing a linear model into logical components to ensure that certain structural preconditions for the existence of an image curve are upheld. Tangential conditions guarantee continuity, while normal conditions select and categorize contrast profiles. The resulting operators allow for coarse measurement of curvilinear differential structure (orientation and curvature) while successfully segregating edge-and line-like features. By thus reducing the incidence of false-positive responses, these operators are a substantial improvement over (thresholded) linear operators which attempt to resolve the same class of features.

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Index Terms:
Edge detection, feature extraction, image processing, computer vision, nonlinear operators.
Citation:
Lee A. Iverson, Steven W. Zucker, "Logical/Linear Operators for Image Curves," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 17, no. 10, pp. 982-996, Oct. 1995, doi:10.1109/34.464562
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