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If you would like to protect yourself from ADA-related claims and lawsuits, then your website must be ADA-accessible.

The best way to make your website ADA accessible is to ensure that your website offers features that allow those who are disabled to use it with ease.

Going over what Optical Character Recognition is and how that affects ADA web accessibility, while speaking with a New York ADA lawyer will make it easier for you to protect your website.

What Is Optical Character Recognition?

The definition of “Optical Character Recognition” – or “OCR,” for short – is as follows: the process of converting visual material into text that can be read, and accessed, by a computer.
Just as an example, if you have a page from a book that you scan into your computer then, with the assistance of OCR technology, all of this text can be transferred onto a PDF document.

If the OCR technology that you use works properly, you can go through this PDF document and, in doing so, access every word individually, even searching for the exact words you want to find.

Why Is Optical Character Recognition Important?

A pre-rendered image that has text within it can be presented with a computer. But, even though this is true, if someone has a disability that prevents them from seeing, they will not be able to access the text on this image.

The reason for the above is as follows: pre-rendered text does not exist as a text image and assistive technologies cannot read the text within a pre-rendered image.

To ensure that those who are disabled can “read” the text on pre-rendered technologies, OCR technology can, and should, be used to turn the text within that image into text that can be read by a computer.

If the text within a pre-rendered image is read by a computer, such as by being placed into a text document, then an assistive technology can read it to someone who is disabled.

Does Optical Character Recognition Affect ADA Web Accessibility?

The answer to the question outlined above is “Yes.”

If your website relies on pre-rendered images of, say, pages from different books, the text within these images must also be accessible in a non-image context.

A good example of the above is a transcript of the text right underneath the image.

The easiest way to produce transcripts of the text that exists within an image is by using OCR technology. But, even though OCR technology is quite reliable, it does not always produce results that are entirely accurate.

You must make sure that the images you are using OCR technology to access/read are crisp, clear, and accessible.

If they are not, then the text you receive will, more often than not, be less than accurate. But, if the images are crisp, clear, and accessible, then the text will be more accurate.

To make sure that the text you have taken from an image is accurate, you must then read it over and correct any errors that you notice.