Results 211 to 220 of about 59,947 (259)
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2013
Mathematical Morphology allows for the analysis and processing of geometrical structures using techniques based on the fields of set theory, lattice theory, topology, and random functions. It is the basis of morphological image processing, and finds applications in fields including digital image processing (DSP), as well as areas for graphs, surface ...
Najman, Laurent, Talbot, Hugues
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Mathematical Morphology allows for the analysis and processing of geometrical structures using techniques based on the fields of set theory, lattice theory, topology, and random functions. It is the basis of morphological image processing, and finds applications in fields including digital image processing (DSP), as well as areas for graphs, surface ...
Najman, Laurent, Talbot, Hugues
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Geography, Mathematics and Mathematical Morphology
2013Mathematical Morphology (MM) has been introduced in geographical sciences during the years 1970-1980. However it did not find the same echo in the geographer community according the areas of research. Unlike remote sensing where MM tools have been used as early as in the eighties and are nowadays widespread, in the research works resorting to spatial ...
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Mathematical morphology on l-images
Signal Processing, 1992Abstract In most applications, morphological operations are considered as unary operations, each associated with a structuring element. Due to the problem of grey-level overflow, the associated structuring elements of morphological operations on grey-level images (functions from R n or Z n to [0, m], where m is a fixed positive number) are ...
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Fuzzy connectivity and mathematical morphology
Pattern Recognition Letters, 1993Summary: We prove an equivalence between the degree of connectedness defined for fuzzy sets and the connection cost defined in the grey-level mathematical morphology framework, starting from the definitions and properties of both concepts.
Isabelle Bloch
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ANALYTICAL MORPHOLOGY: MATHEMATICAL MORPHOLOGY OF DECISION TABLES
Fundamenta Informaticae, 1996We propose a method called analytical morphology for data filtering. The method was created on the basis of some ideas of rough set theory and mathematical morphology. Mathematical morphology makes an essential use of geometric structure of objects while the aim of our method is to provide tools for data filtering when there is no directly available ...
Andrzej Skowron, Lech Polkowski
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2002
Mathematical morphology is a powerful methodology for processing and analysing the shape and form of objects in images. The advances in this area of science allow for application in the digital recognition and modeling of faces and other objects by computers. Mathematical Morphology is comprehensive work that provides a broad sampling
Hugues Talbot, Richard Beare
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Mathematical morphology is a powerful methodology for processing and analysing the shape and form of objects in images. The advances in this area of science allow for application in the digital recognition and modeling of faces and other objects by computers. Mathematical Morphology is comprehensive work that provides a broad sampling
Hugues Talbot, Richard Beare
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Morphological Scale Space and Mathematical Morphology
1999It is well known that a conveniently rescaled iterated convolution of a linear positive kernel converges to a Gaussian. Therefore, all iterative linear smoothing methods of a signal or an image boils down to the application to the signal of the Heat Equation.
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Microarray gridding by mathematical morphology
Proceedings XIV Brazilian Symposium on Computer Graphics and Image Processing, 2002DNA chips (i.e., microarrays) biotechnology is a hybridization (i.e., DNA matching) based process that makes it possible to quantify the relative abundance of mRNA from two distinct samples by analysing their fluorescence signals. This technique requires robotic placement (i.e., spotting) of thousands of cDNAs (i.e., complementary DNA) in an array ...
Roberto Hirata Jr. +3 more
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Cartograms via mathematical morphology
Information Visualization, 2013Visualization of geographic variables as spatial objects of size proportional to variable strength is possible via generating cartograms. We developed a methodology based on mathematical morphology to generate contiguous cartograms. This methodology relies on weighted skeletonization by zone of influence.
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Optoelectronic implementation of mathematical morphology
Optics Letters, 1989An optoelectronic implementation based on optical neighborhood operations and electronic nonlinear feedback is proposed to perform morphological image processing such as erosion, dilation, opening, closing, and edge detection. Results of a numerical simulation are given and experimentally verified.
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