Your SlideShare is downloading. ×
  • Like
Automated SVG Map Labeling for Customizable Large Print Maps for Low Vision Individuals
Upcoming SlideShare
Loading in...5

Thanks for flagging this SlideShare!

Oops! An error has occurred.


Now you can save presentations on your phone or tablet

Available for both IPhone and Android

Text the download link to your phone

Standard text messaging rates apply

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



Published in Technology , Business
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads


Total Views
On SlideShare
From Embeds
Number of Embeds



Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

    No notes for slide


  • 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.