Tactiled: Towards More and Better Tactile Graphics Using Machine Learning

Tactile graphics (TG) can help people with visual disabilities access visual concepts. However, the number of TGs available to users is considerably limited because they need to be created by designers and teachers of the visually impaired (TVIs) with extensive experience. High-quality images can be transformed into TGs. In order to increase the availability of TGs, we trained a machine learning (ML) model that identifies suitable and unsuitable images for TG transformation (See Figure 1). This model would help users identify high-quality images that can be transformed into TGs. The poster presents (1) the ML model trained with 800 images collected from the American Printing House tactile Library and the researchers, (2) a web application that lets TVIs retrain the model by feeding new images and helping with the classification. This system can then be used by anyone, especially parents and teachers, as a filter to produce new TGs.