WebInSight: Making Web Images Accessible

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WebInSightMaking Web Images Accessible

• Jeff Bigham
• Richard Ladner
• Ryan Kaminsky
• Gordon Hempton
• Oscar Danielsson

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Some statistics

• 10 million blind people in the U.S.
• 55,000 blind children
• 5 million blind people over 65
• Computer and Internet Use
• 1 million use computers
• 32 of legally blind adults employed

Source American Foundation for the Blind
Blindness Statistics
http//www.afb.org/Section.asp?SectionID15
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Browsing the web while blind

• Blind users use screen readers
• Alternative text is substituted for images
• When no alternative text provided
• nothing
• filename (060315_banner_253x100.gif)
• link address
• W3C accessibility standards
• Provide a text equivalent for every non-text
  element
• For images with purely visual purpose, a text
  equivalent is an empty string

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Outline

• Web Studies
• WebInSight System
• Where Labels Come From
• Evaluation
• Future Work

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Web Studies

• Images can be significant or insignificant
• Significant images need alternative text
• alt, title, and longdesc HTML attributes
• Insignificant images need empty alternative text
• (spacers, lines, wacky backgrounds, etc.)
• Significance from size, color and function

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Web Studies Groups

• CSE Traffic
• 1 week.
• 11,989,898 images.
• 40.8 significant
• 63.2 assigned alternative text
• Popular/Important Websites
• 500 High-Traffic International Sites
• 100 Top International Universities
• 158 Computer Science Departments
• 137 Federal Agencies
• 50 States plus District of Columbia

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Study Results
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Result Graphs
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Outline

• Web Studies
• WebInSight System
• Where Labels Come From
• Evaluation
• Future Work

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WebInSight

• Add alternative text as a user browses
• Coordinate multiple labeling sources
• Avoid harming the user experience
• Maintain security and privacy

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The Internet
WebInSight Architecture
GET http//www.cs.washington.edu
Login _______ Pass _______
Login _login___ Pass _pass___
Database
GET http//www.cs.washington.edu
GET http//www.cs.washington.edu/
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WebInSight as a Proxy

• Transformation proxy
• Inserts alternative text into webpages
• Inserts AJAX hooks to allow later changes
• Advantages
• Centralized control
• Simple setup and administration
• Disadvantages
• Potentially a bottleneck
• Less control over user interface
• Secure connections dont benefit or are less
  secure

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Outline

• Web Studies
• WebInSight System
• Where Labels Come From
• Evaluation
• Future Work

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Providing Labels Context Labeling

• Many important images are links
• Linked page often describes image
• Function much better than nothing

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Providing Labels OCR Labeling

• Original image not recognized

(No Text)

• Find major colors

• Highlight major colors try again

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Providing Labels OCR Labeling 2

• Color Image OCR Text

(No Text)
(No Text)
(PIC)t
(No Text)
,, ., ,, ,. ,., , ,,, .,,,n(PIC)
(PIC)
Register now!
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Providing Labels OCR Evaluation

• Tested 100 images containing text
• The OCR correctly labeled 52
• Our processing correctly labeled 65

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Providing Labels Human Labeling

• Humans are best labelers
• Luis von Ahns games get people to do it
• WebInSight sends images to such services

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Outline

• Web Studies
• WebInSight System
• Where Labels Come From
• Evaluation
• Future Work

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Evaluation

• Experiment
• Run WebInSight on pages from Web Studies
• 43.2 of unlabelled sig. images labelled
• Of these, 94.1 were correct

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EvaluationUCLA
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Future Work

• User Studies
• Does it help?
• What do users want out of alt text?
• When should WebInSight provide it?
• Refactoring alt text
• Present alt text in the best way possible for
  users
• Tool for Webmasters
• People will always be better but they need help

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Demo