Detecting obstacle-free regions for visual robot navigation by inferring scene horizons

We present preliminary results of an algorithm for detecting obstacle-free regions in indoor environments using both color and texture information for visual robot navigation. By modeling color information in the L*u*v* color space, a color-based segmentation is performed to find similar regions. This segmentation yields a set of regions that are joined together into single areas using texture information. Texture-based similarity measures between segmented regions are computed using ANOVA (Analysis of Variance), which produces the final obstacle-free regions. These regions are then used as visual information to drive a robot towards the scene horizon, i.e. the boundary between visible free space and unexplored areas. The performance of our algorithm was tested on several sequences of images taken from office corridors.