Abstract—This paper presents a novel 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. The algorithm is tested with a challenging indoor and outdoor image set. Test results show that our algorithm performs better than available color based obstacle detection approaches.
Index Terms—Obstacle detection, appearance based obstacle detection, color coherence vector, vision aid.
The authors are with Department of Computer Science and Engineering PEC University of Technology, Chandigarh 160 012, INDIA (e-mail: ajaymittal@pec.ac.in, sanjeevsofat@pec.ac.in).
[PDF]
Cite: Ajay Mittal and Sanjeev Sofat, "A Novel Color Coherence Vector Based Obstacle Detection Algorithm for Textured Environments,"
International Journal of Computer Theory and Engineering vol. 5, no. 1, pp. 81-84, 2013.
