Robust Grayscale Conversion for Vision-Substitution Systems

Abstract

Substitution systems have proved an important potential in mobility assistance for visually disable persons. Particularly, proficient users of auditory-vision substitution are able to identify and reconstruct visual targets. The content of non-visual image is simplified with the purpose to minimize the cognitive process for recognition and also to reduce the duration of the sound patterns. Motivated by these facts, many of the existing substitution systems discard the color information by dealing with grayscale images. This paper presents a robust and effective method of color-to-gray transformation, that preserves the original color contrast of the initial images but also the original saliency. The study is focused taken into consideration the hypothesis that visual salient areas are tightly connected with visual attention. We show that an appropriate translation allows a more accurate rendering of the important image regions but that creates a better mental representation of the environment.