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Issue No. 10 - October (1995 vol. 17)
ISSN: 0162-8828
pp: 982-996
ABSTRACT
<p><it>Abstract</it>—We propose a language for designing image measurement operators suitable for early vision. We refer to them as <it>logical/linear</it> (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.</p>
INDEX TERMS
Edge detection, feature extraction, image processing, computer vision, nonlinear operators.
CITATION
Steven W. Zucker, Lee A. Iverson, "Logical/Linear Operators for Image Curves", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 17, no. , pp. 982-996, October 1995, doi:10.1109/34.464562
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