Titlebook: Mathematical Morphology and Its Applications to Image and Signal Processing; John Goutsias,Luc Vincent,Dan S. Bloomberg Book 2000 Springer

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書目名稱Mathematical Morphology and Its Applications to Image and Signal Processing影響因子(影響力)




書目名稱Mathematical Morphology and Its Applications to Image and Signal Processing影響因子(影響力)學科排名




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書目名稱Mathematical Morphology and Its Applications to Image and Signal Processing網(wǎng)絡(luò)公開度學科排名




書目名稱Mathematical Morphology and Its Applications to Image and Signal Processing被引頻次




書目名稱Mathematical Morphology and Its Applications to Image and Signal Processing被引頻次學科排名




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書目名稱Mathematical Morphology and Its Applications to Image and Signal Processing讀者反饋




書目名稱Mathematical Morphology and Its Applications to Image and Signal Processing讀者反饋學科排名

landfill

From the Sup-Decomposition to A Sequential Decompositionperty of .-operators is that they have a sup-decomposition in terms of a family sup-generating operators, that are parameterized by the operator basis. The sup-decomposition has a parallel structure that usually is not efficient for computation in conventional sequential machines. In this paper, we

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顯赫的人

Minkowski Sum Volume Minimization for Convex Polyhedra one of the shapes can be rotated about arbitrary axis through arbitrary angle. This problem is of interest for some approaches developed for shape pose determination, invariant shape comparison, shape symmetry analysis. It is shown that the problem can be solved efficiently, i.e. there exists a fin

exorbitant

隱藏

A Lattice Control Model of Fuzzy Dynamical Systems in State-Space,mum and infimum. In this paper we introduce a special case of lattice control that can model fuzzy dynamical systems in state space. Vector and signal transformations are represented as lattice dilations or erosions. The state and output responses are computed via supremal convolutions based on fuzz

ARK

macular-edema

臆斷

Affine Invariant Mathematical Morphology Applied to A Generic Shape Recognition Algorithmapes two digital images have in common, up to any affine transform or contrast change. We define as“shape elements” all pieces of level lines of the image. Their number can be drastically reduced by using affine and contrast invariant smoothing Matheron operators, which we describe as alternate affi

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