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Evaluating Barten image metric for predicting character recognition in people with low vision

Evaluating Barten image metric for predicting character recognition in people with low vision. Kimberly A. Schoessow, OTD, OTR/L; Lisa M. Mauney, MS; Mark Uslan, MS; Ronald A. Schuchard, PhD. Aim

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Evaluating Barten image metric for predicting character recognition in people with low vision

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  1. Evaluating Barten image metric for predicting character recognition in people with low vision Kimberly A. Schoessow, OTD, OTR/L; Lisa M. Mauney, MS; Mark Uslan, MS; Ronald A. Schuchard, PhD

  2. Aim • Explore whether Barten square root integral (SQRI) can predict ability of users with low vision to see images on small visual displays (SVDs) on electronic devices. • Relevance • Electronic devices with SVDs are often inaccessible to people with vision loss. • Barten SQRI is image-quality metric already shown to predict whether people with normal vision can see images on cathode ray tube monitor.

  3. Method • Used Barten SQRI and Pelli-Robson Contrast Sensitivity Chart to predict whether 33 people with low vision could recognize low-contrast single digits on screen.

  4. Results • Visual acuity could not significantly predict ability to read low-contrast characters on a display.

  5. Conclusion • Future work: • Explore whether Barten SQRI can predict ability of people with low vision to use actual devices with SVDs.

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