6 Improved Accessibility in Maps for Visually Impaired Users

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This presentation describes a framework of map image analysis and presentation of the semantic information to visually impaired users using alternative modalities (i.e. haptics and audio). The aim of the proposed framework is to provide the visually impaired users with an easy way to use means of accessing conventional 2D maps. The proposed framework utilizes novel algorithms for the segmentation of the map images using morphological filters that are able to provide indexed information on both the street network structure and the positions of the street names in the map. The user can interact with the produced 3D model of the map and examine its properties. The developed framework analyses the map image so as to obtain the enclosed information. While navigating, audio messages are displayed providing information about the current position of the user (e.g. street name).

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6 Improved Accessibility in Maps for Visually Impaired Users

  1. 1. Dr. Dimitrios Tzovaras CERTH/ITI Greece Improved Accessibility in Maps for Visually Impaired Users
  2. 2. <ul><li>Introduction </li></ul><ul><ul><li>Problem Identification </li></ul></ul><ul><ul><li>Related Work </li></ul></ul><ul><ul><li>Proposed Approach </li></ul></ul><ul><li>Haptic exploration of 2D maps </li></ul><ul><ul><li>Prerequisites of the 2D map </li></ul></ul><ul><ul><li>Map image analysis </li></ul></ul><ul><ul><li>Haptic Rendering </li></ul></ul><ul><li>Test Case </li></ul>Overview
  3. 3. <ul><li>Maps are perceived using the visual modality </li></ul><ul><li>Maps are inaccessible for the visually impaired </li></ul><ul><li>Maps are the major means of navigation into unknown spaces </li></ul><ul><li>Visually impaired are not able to use the major means of navigation </li></ul>Problem Identification
  4. 4. <ul><li>A PDA, coupled with an embedded camera, able to recognize road signs </li></ul><ul><li>An automated indoor navigation system, utilizes a camera mounted to the user to capture images from the surroundings </li></ul><ul><li>Scalable Vector Graphics (SVG) maps contain sound effects, assisting the navigation of the visually impaired </li></ul>Related Work There is not any generic framework that enables the exploration of conventional 2D maps for the visually impaired users
  5. 5. <ul><li>A transformation from a conventional 2D map to a multimodal map (haptic and audio) </li></ul><ul><li>Advantages: </li></ul><ul><ul><li>It can be applied to any 2D map that satisfies certain predefined constraints </li></ul></ul><ul><ul><li>The visually impaired users can haptically explore the generated multimodal map </li></ul></ul><ul><ul><li>Audio messages inform the user about the current position on the map </li></ul></ul>Proposed Approach
  6. 6. <ul><li>A haptic-aural representation of the 2D map is created from an image map </li></ul><ul><ul><li>Street names are recognized </li></ul></ul><ul><ul><li>A corresponding pseudo-3D representation is created </li></ul></ul><ul><ul><li>Optical Character Recognition (OCR) as well as </li></ul></ul><ul><ul><li>Text To Speech (TTS) mechanisms are used for the multimodal map generation </li></ul></ul>Haptic Exploration of 2D maps
  7. 7. <ul><li>Prerequisites of the 2D map </li></ul><ul><ul><li>Color constraints : Street names should be presented using a dark color </li></ul></ul><ul><ul><li>Positioning: Street names should be located inside the associated road </li></ul></ul><ul><ul><li>Resolution: Map resolution should be adequate to utilize an OCR algorithm to retrieve street names </li></ul></ul>Map constraints
  8. 8. Map image analysis <ul><li>Road names identification </li></ul><ul><li>Road network structure identification </li></ul><ul><li>3D map model construction </li></ul><ul><li>Road names transformation into speech </li></ul>
  9. 9. <ul><li>1. An erosion filter is applied to the primary image </li></ul><ul><li>2. The produced image is then subjected to thresholding dithering to two colours </li></ul><ul><li>3. Color inversion is applied </li></ul><ul><li>4. A region growing algorithm is applied in order to get the image segments containing the road names. </li></ul>Road names identification
  10. 10. <ul><li>5. A chromatic identity is being given to each segment to enable the identification of each distinct road. </li></ul>Road names identification
  11. 11. <ul><li>Dilation is applied in order to expand the road names </li></ul><ul><li>The angle is being calculated using linear Least Squares </li></ul><ul><li>All street names are discarded from primary map </li></ul><ul><li>Connected operators are applied </li></ul>Road network structure identification
  12. 12. Connected operators <ul><li>Anti-extensive connected operators block diagram </li></ul>
  13. 13. Connected operators Initial map M Binary image of the street name’s regions is T -1 [M] Dilation of M is δ c (M) Outcome of step 1 is g 0
  14. 14. Connected operators <ul><li>e c (g k-1 ) is the erosion of image g k-1 </li></ul><ul><ul><li>Operator max() is applied to e c and M in order to retain regions A and C, but not region B </li></ul></ul><ul><ul><li>Step 2 is iteratively repeated </li></ul></ul>A and C regions are shrunk A and C regions are restored to their primary size Primary image
  15. 15. <ul><li>The two sequential terms g k-1 and g k are being examined </li></ul><ul><ul><li>If </li></ul></ul><ul><ul><li>where N V is the amount of elements of set </li></ul></ul><ul><ul><li>R, C are the dimensions of the image </li></ul></ul><ul><ul><li>T hr is the relative threshold experimentally selected to be T hr = 0.98 </li></ul></ul>Connected operators Initial map M Outcome of the aforementioned iterative procedure
  16. 16. <ul><li>The 3D map is generated as a grooved line map </li></ul><ul><ul><li>this structure is better perceived using a haptic device when compared to a raised line map </li></ul></ul>3D map model construction
  17. 17. Road name transformation into speech
  18. 18. Road name transformation into speech <ul><li>The image that contains only the road names is being generated </li></ul><ul><li>The segment that contains the name of each road is being recognized as well as the angle of the name from the X axis. </li></ul><ul><li>In steps (c) and (d) the corresponding parts of the primary map image containing the road names are being cut. </li></ul>
  19. 19. Road name transformation into speech <ul><li>The segments are first converted into black and white images and then they are being rotated and scaled </li></ul><ul><li>Then they are used by the OCR (Optical Character Recognition) module </li></ul><ul><li>The OCR module outputs the recognized text </li></ul><ul><li>The OCR module passes the recognized text to the TTS (Text-to-Speech) module </li></ul><ul><li>The TTS module transforms text into speech </li></ul>
  20. 20. Haptic Rendering <ul><li>The typical spring-damper model is being used to calculate the force feedback’s magnitude </li></ul><ul><li>The magnitude of the applied force, for a point z that enters the surface is: </li></ul><ul><ul><li>k, is the elasticity constant </li></ul></ul><ul><ul><li>d, is the distance of z from the surface </li></ul></ul>
  21. 21. Test case – 2D primary map loading
  22. 22. Test case – Road names identification
  23. 23. Test case – Road names identification Woodland Dr OCR
  24. 24. Test case – Road network structure identification
  25. 25. Test case – 3D map model construction
  26. 26. Test case – Multimodal map exploration

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