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report_changes_detailed.txt
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report_changes_detailed.txt
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This is a list of more detailed changes.
We changed all British English into American English.
This includes the following words:
emphasise -> emphasize
customisable -> customizable
customisation -> customization
customise -> customize
colour(s) -> color(s)
generalisation -> generalization
neighbour(s) -> neighbor(s)
optimisation -> optimization
initialising -> initializing
behaviour -> behavior
centre(s) -> center(s)
We have also changed many sentences in order to create some extra space for examples of order-k Voronoi diagrams with 1 <= k <= 6.
The detailed changes on a sentence level are located below. For each group of two sentences, the first sentence is the original sentence and the second sentence is the modified sentence.
Note that these sentences are not in any particular order. We also shortened paragraphs where we ended with only a few (<3) words on a new line by removing "filler" words.
In this section, the application refers to the application as a whole, whereas the tool refers to the \textit{tool} page in the application that leverages the capability to generate a Voronoi diagram from an image.
In this section, the application refers to the application as a whole. In contrast, the tool refers to the \textit{tool} page in the application that leverages the capability to generate a Voronoi diagram from an image.
This is quite long and because of it we are not easily able to experiment with many different values.
Because of this rather long rendering time, we are not easily able to experiment with many different values.
We are still not quite satisfied with the Voronoi diagram because some Voronoi [...]
We are still not entirely satisfied with the Voronoi diagram because some Voronoi [...]
Next to the \textit{tool} page which can be used to transform the image into a Voronoi diagram, there are \textit{help} and \textit{about} pages, [...]
Next to the \textit{tool} page, which can be used to transform the image into a Voronoi diagram, there are \textit{help} and \textit{about} pages, [...]
This collection of configuration of parameters results in a highly customisable transformation from image to Voronoi diagram.
This collection of configuration parameters results in a highly customizable transformation from an image to a Voronoi diagram.
Blob detection tries to detecting pixels in an image that differ with respect to specific properties, such as brightness or colour, compared to surrounding pixels \cite{kong2013generalized}.
Blob detection tries to detect pixels in an image that differ with respect to specific properties, such as brightness or color, compared to surrounding pixels \cite{kong2013generalized}.
Consequently, the user can navigate to the \textit{help}, and \textit{about} pages by clicking on the buttons located at (2) and (3) respectively.
Consequently, the user can navigate to the \textit{help} and \textit{about} pages by clicking on the buttons located at (2) and (3), respectively.
After pressing the \textit{submit} button in the dialogue element, all centroids located in the customisable rectangle will be removed from the set of centroids to consider for construction the Voronoi diagram.
After pressing the \textit{submit} button in the dialogue element, all centroids located in the customizable rectangle will be removed from the set of centroids that are used for the construction of the Voronoi diagram.
In our case, the introduction of the order-$k$ Voronoi diagram yields in an additional parameter the user can play around with to construct aesthetically pleasing results.
In our case, the introduction of the order-$k$ Voronoi diagram yields an additional parameter the user can play around with to construct aesthetically pleasing results.
We have tight control on the number of pruned centroids together with the specific approach that is used to prune, [...]
We have tight control over the number of pruned centroids together with the specific approach that is used to prune, [...]
The user can specifcy the percentage of centroids in the graphical user interface.
The user can specify the percentage of centroids in the graphical user interface.
It performs a sampling process where each pixel in the image is subjected to an independent Bernoulli trial which determines whether the pixel becomes a centroid or not with a minimum distance between each centroid.
It performs a sampling process where each pixel in the image is subjected to an independent Bernoulli trial, which determines whether the pixel becomes a centroid or not with a minimum distance between each centroid.
In the graphical user interface, we let the user set a threshold ranging from 1 to 100 that corresponds to the threshold used by FAST.
In the graphical user interface, we let the user set a threshold ranging from 1 to 100, which corresponds to the threshold used by FAST.
This is less so the case for \textit{corner detection} and is likely because \textit{corner detection} leads to a lower number of centroids compared to these other methods.
This occurs less for \textit{corner detection} and is likely because \textit{corner detection} leads to a lower number of centroids compared to these other methods.
Furthermore, it can easily be extended into an order-$k$ Voronoi diagram as we will see later.
Furthermore, it can easily be extended into an order-$k$ Voronoi diagram, as we will see later.
The result of a transformation from an image to a Voronoi diagram should be customisable such that the user can modify the result to their liking.
The result of a transformation from an image to a Voronoi diagram should be customizable such that the user can modify the result to their liking.
J.W. van Lith, N.P.M. van de Waterlaat, and J.C.W. van Winden
John van Lith, Nick van de Waterlaat, Jurriën van Winden
We also consider an alternative definition where a Voronoi region is defined as the set of pixels having a particular set of $k$ centroids as its $k$ nearest neighbors. This alternative definition results in Voronoi regions that represent combinations of centroids and will result in a different Voronoi diagram compared to the ordinary order-$k$ Voronoi diagram.
Commented this out in the introduction since we don't use it
It also contains information about where the application is hosted and a reference to both the source code and this paper.
Removed this sentence.
Since we are satisfied with the render of illustrated in Figure 9b, we decide to save it by pressing the save button in the top-right corner of the result component.
Since we are satisfied with the render of illustrated in Figure 9b, we decide to save it by pressing on the save button.