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Automated SVG Map Labeling for Customizable Large Print Maps for Low Vision Individuals
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Automated SVG Map Labeling for Customizable Large Print Maps for Low Vision Individuals

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  • 1. Automated SVG Map Labeling for Customizable Large Print Maps for Low Vision Individuals Vladimir Kulyukin 1 James Marston 2 Joshua Miele 3 Aliasgar Kutiyanawala 1 1 Department of Computer Science, Utah State University 2 Atlanta VA Rehabilitation R&D Center for Vision Loss 3 Smith-Kettlewell Eye Research Institute Abstract Algorithm: Step 1 – Aggregate Street Segments Algorithm: Step 5 – Shift Candidate Label PositionsMany people with visual impairments do not read Braille and have problems Segment 4 Segme nt 5interpreting tactile information. Some of them have enough residual vision so that if ent 3 mstreets and their names were presented in the proper color, size, and style, they Seg e nt 2could benefit from customizable large print maps. Such maps would allow people Segmwith low vision to study a new area, pre-plan travel, and have portable maps to m ent 1 Segconsult while navigating in unfamiliar areas. This paper presents an algorithm forplacing street names on street maps produced by the Tactile Map AutomatedProduction (TMAP) software in the Scalable Vector Graphics (SVG) format. Aggregated Segment 2 SVG Map Labelling Problem ent 1 gm ted Se rega Agg Algorithm: Step 2 – Compute Label Regions Input: ) Ab ove ( on egi el R L ab ) Be low n ( egio el R L abPart of the SVG map of downtown Chicago that the algorithm takes as inputdescribed in the paper. It contains the street lines but no street names. The streetnames are given as attributes of street segments in the SVG file and are not properly Resultsplaced. Algorithm: Step 3 – Reduce the Label Information Overload If a label region is smaller than the label, the label is iteratively reduced as follows: Overall Map Color 1) Using standard abbreviations: Drive becomes Dr. 2) Removing all vowels: Way becomes Wy Street Line Size 3) Iteratively removing last character Google Maps Our Algorithm Street Name Color Output: Algorithm: Step 4 – Score Candidate Label Positions Font Style Font Size 0 0.5 1 1.5 2 2.5 3 3.5 AcknowledgementsPart of the SVG map of downtown Chicago generated by the algorithm described inthe paper. The streets form a grid of lines. The street lines are in red, the street The first author would like to acknowledge that this research has been supported, innames are in green. The street line widths and colors, the font style, size, and color part, through NSF grant IIS-0346880, and several Community University Researchcan be changed by the user. Initiative (CURI) grants from the State of Utah.