Text legibility in augmented reality with optical see-through displays can be challenging due to the interaction with the texture on the background. Literature presents several approaches to predict legibility of text superimposed over a specific image, but their validation with an AR display and with images taken from the industrial domain is scarce. In this work, we propose novel indices extracted from the background images, displayed on an LCD screen, and we compare them with those proposed in literature designing a specific user test. We collected the legibility user ratings by displaying white text over 13 industrial background images to 19 subjects using an optical see-through head-worn display. We found that most of the proposed indices have a significant correlation with user ratings. The main result of this work is that some of the novel indices proposed had a better correlation than those used before in the literature to predict legibility. Our results prove that industrial AR developers can effectively predict text legibility by simply running image analysis on the background image.

Predicting Text Legibility over Textured Digital Backgrounds for a Monocular Optical See-Through Display

Manghisi, Vito Modesto;Gattullo, Michele;Fiorentino, Michele;Uva, Antonio Emmanuele;Marino, Francescomaria;Bevilacqua, Vitoantonio;Monno, Giuseppe
2017

Abstract

Text legibility in augmented reality with optical see-through displays can be challenging due to the interaction with the texture on the background. Literature presents several approaches to predict legibility of text superimposed over a specific image, but their validation with an AR display and with images taken from the industrial domain is scarce. In this work, we propose novel indices extracted from the background images, displayed on an LCD screen, and we compare them with those proposed in literature designing a specific user test. We collected the legibility user ratings by displaying white text over 13 industrial background images to 19 subjects using an optical see-through head-worn display. We found that most of the proposed indices have a significant correlation with user ratings. The main result of this work is that some of the novel indices proposed had a better correlation than those used before in the literature to predict legibility. Our results prove that industrial AR developers can effectively predict text legibility by simply running image analysis on the background image.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/117174
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 2
social impact