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The quality of modern electron microscopes, such as SEM, STEM, and TEM, has greatly improved. However, the quality of the experimental images produced by these instruments is often compromised by stochastic and deterministic distortions arising from the instrument or its environment1,2,3. These dis...
often machine-dependent, developed for a time-consuming integration of valuable data. Scanning electron microscopy (SEM) is one of those methodologies of characterisation for which the number of observations of a given material is limited to just a few...
The main target of this paper is fruit skin patterns such as jackfruit and lychee covered by tessellation patterns in which each cell contains a unique spike dot that can be considered as a generator. The problem of estimating the weights is reduced to an optimization problem, and can be ...
Once these locations are estimated, we have a set of point-referenced predictor location in the domain of interest. The domain is then subjected to regular square tessellation such that each pixel contains at most one location—essentially rewriting the point process a posteriori as superposition of...
The Voronoi tessellation [47] associated to this point cloud allows to match every detected curve to its most likely ground truth. If the distance to the matched ground truth is less than a determined threshold, then the corresponding curve is considered detected; otherwise, it is a “false”...
The main focus of this article is to present a new tessellation model which can be applied to model the shape characteristics of the aluminium grain images. One special feature of the new tessellation model is that it is capable of generating tessellation patterns having rough boundaries. Some ...
Low-level regions that cannot be classified with the necessary certainty are passed to a second stage, where - embedded in their respective environment - they are compared with structural patterns deduced from anatomical knowledge. The tooth segmentation takes the coarse-grained tessellation as its ...
Grain generation in 2D is performed using the Voronoi tessellation method75, which is one of the available techniques for producing random polygonal grains within a domain. This process starts by randomly selecting a number of points within the range [15, 175]. Each grain image is created by ...