Best Linear Unbiased Estimators for Properties of Digitized Straight Lines
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision, Graphics, and Image Processing
Morphological methods in image and signal processing
Morphological methods in image and signal processing
A Representation Theory for Morphological Image and Signal Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multiscanning Approach Based on Morphological Filtering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Spectrum and Multiscale Shape Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Natural Representations for Straight Lines and the Hough Transform on Discrete Arrays
IEEE Transactions on Pattern Analysis and Machine Intelligence
The algebraic basis of mathematical morphology. I. dilations and erosions
Computer Vision, Graphics, and Image Processing
The analysis of morphological filters with multiple structuring elements
Computer Vision, Graphics, and Image Processing
The algebraic basis of mathematical morphology
CVGIP: Image Understanding
Morphological Filtering as Template Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Algorithms for the Decomposition of Gray-Scale Morphological Operations
IEEE Transactions on Pattern Analysis and Machine Intelligence
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P. Maragos (1989) provided a framework for the decomposition of many morphologic operations into orthogonal components or basis sets. Using this framework, a method to find the minimal basis set for the important operation of closing in two dimensions is described. The closing basis sets are special because their elements are members of an ordered, global set of closing shapes or primitives. The selection or design of appropriate individual or multiple structuring elements for image filtering can be better understood, and sometimes implemented more easily, through consideration of the orthogonal closing decomposition. Partial closing of images using ordered fractions of a closing basis set may give a finer texture or roughness measure than that obtained from the conventional use of scaled sets of shapes such as the disc. The connection between elements of the basis set for closing and the complete, minimal representation of arbitrary logic functions is analyzed from a geometric viewpoint.