Different imageprocessing techniques have recently been investigated for the characterization of complex porous media, such as bones, stones and soils. Among these techniques, 3D thinning algorithms are generally use...
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Different imageprocessing techniques have recently been investigated for the characterization of complex porous media, such as bones, stones and soils. Among these techniques, 3D thinning algorithms are generally used to extract a one-voxel-thick skeleton from 3D porous objects while preserving the topological information. Models based on simplified skeletons have been shown to be efficient in retrieving morphological information from large scale disordered objects not only at a global level but also at a local level. In this paper, we present a series of 3D skeleton-based imageprocessing techniques for evaluating the micro-architecture of large scale disordered porous media. The proposed skeleton method combines curve and surface thinning methods with the help of an enhanced shape classification algorithm. Results on two different porous objects demonstrate the ability of the proposed method to provide significant topological and morphological information. (C) 2013 IMACS. Published by Elsevier B.v. All rights reserved.
The presence of metal artifacts in dental CT prevents the correct exploration and planning of dental interventions. This paper addresses a new paradigm in metal artifact reduction that uses the backprojected data avai...
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ISBN:
(纸本)9781457713033
The presence of metal artifacts in dental CT prevents the correct exploration and planning of dental interventions. This paper addresses a new paradigm in metal artifact reduction that uses the backprojected data available in the DICOM files. The method, based on variational image registration and morphological lambda reconstruction, enhances the image quality using not only the information of the artifacted image (horizontal approach) but also the information of adjoining images (vertical approach). Some preliminary results involving different CT scanners and patients are presented and discussed.
The adsorption abilities of cotton cellulose fibers are very often modified by alkaline treatments in form of alkaline purification or mercerization using high concentration of NaOH. We tried to determine the correlat...
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The adsorption abilities of cotton cellulose fibers are very often modified by alkaline treatments in form of alkaline purification or mercerization using high concentration of NaOH. We tried to determine the correlation between morphological modifications and the adsorption abilities of cotton fibers using several methods: the analysis of microscope images of fibers by imageprocessing and the analysis of the electrokinetic surface properties which express the adsorption behavior of fibers. The longitudinal images and cross-sections of native and modified cotton fibers were analyzed and the parameters: form factor, wall thickness, cross-section area, fiber diameter, lumen area were calculated using imageprocessing. The adsorption behavior of native and NaOH modified polymers was investigated by the determination of electrokinetic properties. The zeta potential (zeta) was calculated from streaming potential measurements as a function of pH and surfactant concentration in the Liquid phase. The results indicate that only a correct combination between the morphological modifications and electrokinetic behavior of fibers leads to a desirable adsorption mechanism which causes a specific adsorption of components of the liquid phase.
This contribution deals with the textured images segmentation. The model exploits morphological operators and order filters properties. A morphological decomposition filters bank is built to isolate elementary pattern...
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We propose a software architecture for picture processing that allows efficient memory management when algorithms with many operators are applied to large images, and that allows automated parallelization. This archit...
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ISBN:
(纸本)0819419273
We propose a software architecture for picture processing that allows efficient memory management when algorithms with many operators are applied to large images, and that allows automated parallelization. This architecture relies on image tiling and operators with a call back function that evaluates image tiles on demand. Several tiling strategies with and without overlapping are discussed. The compexity of this evaluation strategy is hidden to application programs. This is shown with a sample program. This architecture is well suited for neighborhood operators such as convolutions and mathematical morphology operators.
morphological associative memories (MAMs) form a subclass of morphological neural networks. Storage and recall in MAMs is realized using the matrix numerical operations of minimax algebra in a similar fashion as the c...
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ISBN:
(纸本)0889863784
morphological associative memories (MAMs) form a subclass of morphological neural networks. Storage and recall in MAMs is realized using the matrix numerical operations of minimax algebra in a similar fashion as the classic correlation encoding technique. The kernel method, based upon strong morphological independence of the exemplar pattern set, allows to combine two MAMs for enhancing the recall capability when dealing with non-boolean patterns corrupted by random uniform noise. This paper describes a new procedure for assigning a kernel to any set of exemplar patterns that are restricted to have non-negative entries over a finite set of values. Thus, our attention is focused to the specific case of grayscale images and we show, by means of illustrative examples, the recollection capability of the kernel based morphological associative memory scheme including a probabilistic model for its performance.
Brain Tumor is the unconstrained growth of bizarre cells in brain. In this work, dicom Magnetic Resonance image (MRI) is taken as an input and tried to extract tumor cells from the input image. Pre-processing techniqu...
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ISBN:
(纸本)9781538635216
Brain Tumor is the unconstrained growth of bizarre cells in brain. In this work, dicom Magnetic Resonance image (MRI) is taken as an input and tried to extract tumor cells from the input image. Pre-processing technique is used to remove noise from image. To this image, k-means clustering is applied and from this clustered image, skull was removed using morphological operations to identify tumor cells easily. Finally, image thresholding is applied to this image followed by levelset segmentation to extract tumor cells. Performance matrices like true positive (TP), true negative (TN), false positive (FP), false negative (FN), precision and recall to measure the accuracy of our results, is also evaluated.
In this paper we use concepts from the lattice-based theory of morphological operators and fuzzy sets to develop generalized lattice image operators that can be expressed as nonlinear convolutions that are suprema or ...
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ISBN:
(纸本)0780367251
In this paper we use concepts from the lattice-based theory of morphological operators and fuzzy sets to develop generalized lattice image operators that can be expressed as nonlinear convolutions that are suprema or infima of fuzzy intersection or union norms. Our emphasis (and differences with previous works) is the construction of pairs of fuzzy dilation and erosion operators that form lattice adjunctions. This guarantees that their composition will be a valid algebraic opening or closing. The power but also the difficulty in applying these fuzzy operators to image analysis is the large variety of fuzzy norms and the absence of systematic ways in selecting them. Towards this goal, we have performed extensive experiments in applying these fuzzy operators to various nonlinear filtering and image analysis tasks, attempting first to understand the effect that the type of fuzzy norm and the shape-size of structuring function have on the resulting new image operators. Further, we have developed some new fuzzy edge gradients and optimized their usage for edge detection on test problems via a parametric fuzzy norm.
This paper proposes a design of cell circuits for implementing cellular-automaton devices that perform morphological picture processing. To produce the complex cell functions required for the morphologicalprocessing,...
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This paper proposes a design of cell circuits for implementing cellular-automaton devices that perform morphological picture processing. To produce the complex cell functions required for the morphologicalprocessing, we present the idea of using the silicon functional device, v-MOS FET. We designed sample cell circuits for several morphologicalprocessings, and simulated their operation to show the expected cell operation. We also designed a sample cellular-automaton circuit using the proposed cell circuits, and demonstrated in simulation its example processing (noise cleaning and edge extraction in an image). A low dissipation of about 20 mu W per cell circuit can be expected at 1 MHz operation;therefore, 10(5) or more cells that operate in parallel can be integrated into an LSI. (C) 1998 Elsevier Science Ltd. All rights reserved.
images are soft copies of real world objects. image can be represented in the area of digital processing, which can be said as another reproduction of an object. Basically Segmentation is one of the processes of parti...
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ISBN:
(纸本)9781509012855
images are soft copies of real world objects. image can be represented in the area of digital processing, which can be said as another reproduction of an object. Basically Segmentation is one of the processes of partitioning a digital image into multiple regions and extracting meaningful regions for the future image analysis. The prime objective of this research work is to segment the abnormal HIv cells in blood using morphological operations. The boundary region of the HIv cells in blood is detected and segmented using different morphological operations. Finally image Quality Assessment(IQA) has been carried out using various evaluation measures.
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