6 Improved Accessibility in Maps for Visually Impaired Users

27-28 March 2010, Paphos, Cyprus

FOSS-AMASatellite event

Dr. Dimitrios TzovarasCERTH/ITI

Greece

Improved Accessibility in Maps for Visually Impaired

Users


FOSS-AMASatellite event Overview

Introduction◦ Problem Identification◦ Related Work◦ Proposed Approach

Haptic exploration of 2D maps◦ Prerequisites of the 2D map ◦ Map image analysis◦ Haptic Rendering

Test Case


FOSS-AMASatellite event Problem Identification

Maps are perceived using the visual modality

Maps are inaccessible for the visually impaired

Maps are the major means of navigation into unknown spaces

Visually impaired are not able to use the major means of navigation


FOSS-AMASatellite event Related Work

A PDA, coupled with an embedded camera, able to recognize road signs

An automated indoor navigation system, utilizes a camera mounted to the user to capture images from the surroundings

Scalable Vector Graphics (SVG) maps contain sound effects, assisting the navigation of the visually impaired

There is not any generic framework There is not any generic framework that enables the exploration of that enables the exploration of conventional 2D maps for the visually conventional 2D maps for the visually impaired usersimpaired users


FOSS-AMASatellite event Proposed Approach

A transformation from a conventional 2D map to a multimodal map (haptic and audio)

Advantages:

◦ It can be applied to any 2D map that satisfies certain predefined constraints

◦ The visually impaired users can haptically explore the generated multimodal map

◦ Audio messages inform the user about the current position on the map


FOSS-AMASatellite event Haptic Exploration of 2D maps

A haptic-aural representation of the 2D map is created from an image map◦ Street names are recognized

◦ A corresponding pseudo-3D representation is created

◦ Optical Character Recognition (OCR) as well as

◦ Text To Speech (TTS) mechanisms are used for the multimodal map generation


FOSS-AMASatellite event Map constraints

Prerequisites of the 2D map

◦ Color constraints: Street names should be presented using a dark color

◦ Positioning: Street names should be located inside the associated road

◦ Resolution: Map resolution should be adequate to utilize an OCR algorithm to retrieve street names


FOSS-AMASatellite event Map image analysis

1. Road names identification

2. Road network structure identification

3. 3D map model construction

4. Road names transformation into speech


FOSS-AMASatellite event Road names identification

1. An erosion filter is applied to the primary image

2. The produced image is then subjected to thresholding dithering to two colours

3. Color inversion is applied

4. A region growing algorithm is applied in order to get the image segments containing the road names.


FOSS-AMASatellite event Road names identification

5. A chromatic identity is being given to each segment to enable the identification of each distinct road.


FOSS-AMASatellite event Road network structure identification

Dilation is applied in order to expand the road names The angle is being calculated using linear Least Squares All street names are discarded from primary map Connected operators are applied


FOSS-AMASatellite event Connected operators

Anti-extensive connected operators block diagram



Initial map M

Binary image of the street name’s regions is T-1[M]

Dilation of M is δc(M)

Outcome of step 1 is g0



ec(gk-1) is the erosion of image gk-1

◦ Operator max() is applied to ec and M in order to

retain regions A and C, but not region B◦ Step 2 is iteratively repeated

A and C regions are shrunk

A and C regions are restored to their primary size

Primary image



The two sequential terms gk-1 and gk are being examined◦ If

◦ where NV is the amount of elements of set

◦ R, C are the dimensions of the image

◦ Thr is the relative threshold experimentally selected to be Thr =

0.98

Initial map M Outcome of the aforementioned iterative procedure


FOSS-AMASatellite event 3D map model construction

The 3D map is generated as a grooved line map ◦ this structure is better perceived using a haptic device

when compared to a raised line map



Road name transformation into speech




a. The image that contains only the road names is being generated

b. The segment that contains the name of each road is being recognized as well as the angle of the name from the X axis.

c. In steps (c) and (d) the corresponding parts of the primary map image containing the road names are being cut.




e. The segments are first converted into black and white images and then they are being rotated and scaled

f. Then they are used by the OCR (Optical Character Recognition) module

g. The OCR module outputs the recognized text

h. The OCR module passes the recognized text to the TTS (Text-to-Speech) module

i. The TTS module transforms text into speech


FOSS-AMASatellite event Haptic Rendering

The typical spring-damper model is being used to calculate the force feedback’s magnitude

The magnitude of the applied force, for a point z that enters the surface is:

o k, is the elasticity constant o d, is the distance of z from the surface


FOSS-AMASatellite event Test case – 2D primary map loading


FOSS-AMASatellite event Test case – Road names

identification


FOSS-AMASatellite event Test case – Road names

identification

Woodland DrOCR


FOSS-AMASatellite event Test case – Road network

structure identification


FOSS-AMASatellite event Test case – 3D map model

construction


FOSS-AMASatellite event Test case – Multimodal map

exploration

Technology

6 Improved Accessibility in Maps for Visually Impaired Users