Obstacle detection is a main key of autonomous vehicles. When communicating with huge robots in unstructured background, resilient obstacle detection is required. Few of the existing methods are mainly suited for the backgrounds in which the ground is comparatively flat and with roughly the same color throughout the terrain. A novel procedure proposed in the work presented here uses a monocular camera, for real-time performance. We compute the homography between two successive frames by computing the fundamental matrix between the two frames. Estimation of fundamental matrix is followed by triangulation so as to estimate the distance of the object from the camera. An obstacle detection and distance estimation system based on visual particular attribute and stereo vision is hence discussed in the presented work.

1. James Bruce, Tucker Balch and Manuela Veloso, "Fast and Inexpensive Color Image Segmentation for Interactive Robots" Proceedings of the 2000 IEEE International Conference on intelligent Robots and Systems.
2. Iwan Ulrich and IllahNourbakhsh, "Appearance-Based Obstacle Detection with Monocular Color Vision" Proceedings of the AAAI National Conference on Artificial Intelligence, Austin, TX, July/August 2000.
3. Parag H. Batavia and SanjivSingh, "Obstacle Detection Using Adaptive Color Segmentation and Color Stereo Homography" Carnegie Mellon University Robotics Institute Pittsburgh 2004.
4. T. A. Brown and J. Koplowitz. , "The weighted nearest neighbor rule for class dependent s sample sizes" IEEE Transactions on Information Theory, 2003.
5. CARLA E. BRODLEY, PAUL E. UTGOFF, "Multivariate Decision Trees" Kluwer Academic Publishers, Boston. Manufactured in The Netherlands 1998.
6. J. Borenstein1, H. R. Everett2, L. Feng3, and D. Wehe, "Mobile Robot Positioning & Sensors and Techniques" 2000.
7. H. D. Chang, X. H. ziangand JingliWang,"Color image Segmentation" Dept of computer science Utah State of university 2003.
8. Richard I Hartley, "A High-Performance Stereo System for Obstacle Detection," Carnegie Mellon University Doctoral Dissertation, CMU-RI-TR-98-24, September, 1998.
9. Dakopoulos, D. , Bourbakis, N. G. , "Wearable obstacle avoidance electronic travel aids from blind" IEEE Trans 2010.
10. Cheng-Lung Lee a,*, Chih-Yung Chen a, Peng-Cheng Sung a, Shih-Yi Lu, "Assessment of a simple obstacle detection device for the visually impaired" 2013 Elsevier Ltd and The Ergonomics Society.
11. M. Veloso, E. Winner, S. Lenser, J. Bruce, and T. Balch. , "Vision-Servoed Localization and Behaviors for an Autonomous Quadruped Legged Robot" Artificia1 Intelligence Planning Systems, 2000
12. Long CHEN, Bao-long GUO, Wei SUN. , "Obstacle detection system for visually impaired people based on stereo vision" Fourth International Conference on Genetic and Evolutionary Computing 2010.

Image Segmentation Centroid Thresholding Fundamental Matrix Triangulation.