This feature is in line with the PowerPoint Designer feature, in terms of take text only content and make it visual for me. The Picture Slides Lab tool automates making text stylized over an image (inserted image or background image). PowerPointLabs is an entire ribbon, with a lot of good design, layout and styling features.įor this post I am just going through one of several styling options that stood out. I do recommend spending time going through the tutorial walk-through that is available after the add-in is installed.
POWERPOINT LAB SKELETONS CBC TEMPLATE FULL
When we tested PowerPointLabs it was FREE, and full of features, many we have not seen in any other offering. ACM 27(3):236–239.We continue our March Blog Posts on PowerPoint Add-ins with PowerPointLabs. A fast parallel algorithm for thinning digital patterns.
POWERPOINT LAB SKELETONS CBC TEMPLATE SERIES
Figure 4 presents a series of generated m’s. Each chosen typeface had a colour and a shape associated. To each generated typeface we could determine which typefaces we wanted as input an how many and the used colours and modules. The filling of each stroke is composed of the repetition of modules along the stroke line. circles, triangles, squares, or abstract shapes) repeatedly we fill the strokes of the final skeletons and generate typefaces using different colours and transparencies. With this measure, we can replicate the glyph, or increase or decrease the weight proportionally. Therefore, when calculating the distance between each the pixel of the extracted skeleton to the nearest pixel from the border, we determine the width of the original typeface. The first step of this project, the extraction process, started with the exclusion of the pixels furthest from the centre of the shape.
The last part of the process was the development of the structure of the glyphs. Figure 3 presents generated skeletons by the recombination of different typefaces, each colour represents a different input typefaceĮxamples of generated skeletons by the recombination of different typefaces In the end, we had, for a given character, several versions/skeletons for each stroke. When the compared parts had a similar angular velocity and centre point, they were considered corresponding. Then, each of these parts was compared with all the constituent parts of the second skeleton and so on. The association process started with the ordering of the strokes of the first skeleton, from the longest to the shortest length. The central point is an average of all points of the part in question. To put it in context, angular velocity is a vector that represents the process of changing the orientation of a given line. Therefore, each stroke did not need to be totally equal to the other to be associated. To do that we determined the angular velocity and the central point for each of skeleton. To each glyph we needed to assess which were the strokes of each skeleton could be associated with each other.
Since we already had a system that generated skeletons, the next step was the combination of parts between different skeletons. The extraction of the skeleton of an ‘h’ and its posterior division into strokes The circles highlight the border points and a different colour was applied to differentiate the different parts detected. Figure 2 presents the process of skeleton extraction and division into parts of an ‘h’. We scanned all the points of the skeleton and when we found a border point we created a new stroke, and so on till the end. A stroke is composed by a list of points, but in general, they are more two and a set of strokes compose a skeleton. After analyzing the generated skeletons, we noticed that when a point was part of three segments it divides different strokes of the skeleton. With the skeletons extracted, we needed to find a method that identified the different parts. We decided to use Zhang-Suen Thinning Algorithm that aims to extract the structural lines of a binary image, so it is ideal for our case, the skeleton extraction. Therefore, we make sure that the design of the glyphs follows the rules of tradition font design.
For that, we decided to start by extraction existing fonts skeleton. Our first goal was the generation of the typeface structure. The development of the structure of the glyphs For this, three aspects were worked out: (i) the development of the structure of the typefaces generated and the codification of the different elements of the anatomy of the letter in different layers (ii) the combination of layers of different typefaces and (iii) the creation of fonts through the generation/ modification of the elements of these layers. In this work, we present a computer system that design fonts in a generative way. The choice and use of font gives indications regarding the subject we are addressing. For graphic designers, the use of typefaces is crucial to create messages and add layers of content.
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