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Generic Implementation Of Morphological Image Operators
 In Mathematical Morphology, Proc. of ISMM
, 2002
"... Several libraries dedicated to mathematical morphology exist. But they lack genericity, that is to say, the ability for operators to accept input of di#erent natures 2D binary images, graphs enclosing floating values, etc. We describe solutions which are integrated in Olena, a library providing m ..."
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Cited by 6 (2 self)
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Several libraries dedicated to mathematical morphology exist. But they lack genericity, that is to say, the ability for operators to accept input of di#erent natures 2D binary images, graphs enclosing floating values, etc. We describe solutions which are integrated in Olena, a library providing morphological operators. We demonstrate with some examples that translating mathematical formulas and algorithms into source code is made easy and safe with Olena. Moreover, experimental results show that no extra costs at runtime are induced.
Beating C in Scientific Computing Applications On the Behavior and Performance of LISP, Part 1
"... This paper presents an ongoing research on the behavior and performance of LISP with respect to C in the context of scientific numerical computing. Several simple image processing algorithms are used to evaluate the performance of pixel access and arithmetic operations in both languages. We demonstr ..."
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This paper presents an ongoing research on the behavior and performance of LISP with respect to C in the context of scientific numerical computing. Several simple image processing algorithms are used to evaluate the performance of pixel access and arithmetic operations in both languages. We demonstrate that the behavior of equivalent LISP and C code is similar with respect to the choice of data structures and types, and also to external parameters such as hardware optimization. We further demonstrate that properly typed and optimized LISP code runs as fast as the equivalent C code, or even faster in some cases.
A Parallel Algorithmic Pattern
, 2003
"... This paper briefly discuss the general class of algorithms that can be implemented using parallel constructions. Common characteristics of these algorithms are also described in order to provide a generic representation for parallel algorithms. In addition it describes the parallel pattern in terms ..."
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This paper briefly discuss the general class of algorithms that can be implemented using parallel constructions. Common characteristics of these algorithms are also described in order to provide a generic representation for parallel algorithms. In addition it describes the parallel pattern in terms of image scannings and its relationship within mathematical morphology. Such a pattern is essential for the development of morphological operators and operations. Examples of the application of the parallel generic pattern are given for both scalar lattices and nonscalar lattices. Scalar lattices are used to give a parallel pattern representation for real values, parabolic morphology, and bbit integers. Nonscalar lattices are restricted to color lattices. Each case study presented in this paper match the generic representation of the parallel pattern.
Writing Reusable Digital Topology Algorithms in a Generic Image Processing Framework
"... Digital Topology software should reflect the generality of the underlying mathematics: mapping the latter to the former requires genericity. By designing generic solutions, one can effectively reuse digital topology data structures and algorithms. We propose an image processing framework focused on ..."
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Digital Topology software should reflect the generality of the underlying mathematics: mapping the latter to the former requires genericity. By designing generic solutions, one can effectively reuse digital topology data structures and algorithms. We propose an image processing framework focused on the Generic Programming paradigm in which an algorithm on the paper can be turned into a single code, written once and usable with various input types. This approach enables users to design and implement new methods at a lower cost, try crossdomain experiments and help generalize results.