Obstacle Detection in Textured Environment by using Color Coherence

Obstacle detection algorithm that makes use of color information and color coherence vectors for robust obstacle detection. The algorithm makes use of color cue to classify a pixel in an image as an obstacle or a path. Color is one of the prominent image features. Color information is readily available as input from a color camera. Our algorithm makes use of coherence vectors for representation and matching instead of histograms. A color histogram provides no spatial information. It merely describes the color information present in an image. Color coherence vectors represent pixels as either coherent or incoherent. Color coherence vectors prevent coherent pixels from getting matched with incoherent pixels. The color histogram cannot make such fine distinction. This paper a novel algorithm for obstacle detection is proposed that makes use of color cue and color coherence vectors for robust obstacle detection. The algorithm detects obstacles based on the appearance of individual pixels. Whether an individual pixel belongs to an obstacle or a navigable path is determined by a color classifier. The coherence vectors are better than histograms as they incorporate spatial information. Moreover, our approach does not have any learning requirement prior to the use of classifier.