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Real-Time Horizon Line Detection based on Fusion of Classification and Clustering
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 121 - Number 10 |
| Year of Publication: 2015 |
| Authors: Ali Pour Yazdanpanah, Emma E. Regentova, Venkatesan Muthukumar, George Bebis |
10.5120/21574-4625
|
Ali Pour Yazdanpanah, Emma E. Regentova, Venkatesan Muthukumar, George Bebis . Real-Time Horizon Line Detection based on Fusion of Classification and Clustering. International Journal of Computer Applications. 121, 10 ( July 2015), 5-11. DOI=10.5120/21574-4625
Abstract
Horizon line detection is a demanding problem in various tasks associated with planet exploration, because no standard approaches such as global positioning system is available. Horizon line is a boundary line defined between a sky and non-sky region in 2D images, and it is an important visual clue that can be utilized for calculating the rover's position and orientation during planetary missions. The problem of segmenting an image into sky and non-sky regions is classically referred as "horizon line detection". Subsequently, the localization problem can be solved by matching the detected horizon line in 2D images with virtually generated horizon lines from 3D terrain patterns. In this paper, we propose a new real-time horizon line detection (HLD) method by coupling clustering and classifications, as well as implementing the algorithm on the NVIDIA's compute unified device architecture (CUDA). The proposed method has been evaluated on NASA Basalt Hill dataset and on a set of mountainous images that have been collected from the web. The experiments demonstrate high accuracy in determining the horizon line that is proven by provided Receiver Operating Characteristic (ROC) curves.
References
- Boroujeni N. S. , Etemad S. A. , Whitehead A. 2012 Robust Horizon Detection Using Segmentation for UAV Applications. Proceedings of IEEE Ninth Conference on Computer and Robot Vision.
- McGee T. G. , Sengupta R. , and Hedrick K. 2005 Obstacle Detection for Small Autonomous Aircraft Using Sky Segmentation. Proceedings of International Conference on Robotics and Automation (ICRA).
- Thurrowgood S. , Soccol D. , Moore R. J. D. , Bland D. , and Srinivasan M. V. 2009 A Vision Based System for Altitude Estimation of UAVs. Proceedings of International Conference on Intelligent Robots and Systems (IEEE/RSJ).
- De Croon G. C. H. E. , Remes B. D. W. , DeWagter C. , and Ruijsink R. 2011 Sky Segmentation Approach to Obstacle Avoidance. IEEE Aerospace Conference.
- Ettinger S. M. , Nechyba M. C. , Ifju P. G. , and Waszak M. 2002 Vision- Guided Flight Stability and Control for Micro Air Vehicles. Proceedings of International Conference on Intelligent Robots and Systems (IEEE/RSJ).
- Todorovic S. , Nechyba M. C. , Ifju P. G. 2003 Sky/Ground Modeling for Autonomous MAV Flight. Proceedings of International Conference on Robotics and Automation (ICRA).
- Baatz G. , Saurer O. , Koser K. , and Pollefeys M. 2012 Large Scale Visual Geo-Localization of Images in Mountainous Terrain Proceedings of European Conference on Computer Vision.
- Liu W. and Su C. 2014 Automatic Peak Recognition for Mountain Images Advanced Technologies, Embedded and Multimedia for Human-centric Computing.
- Fefilatyev S. , Smarodzinava V. , Hall L. O. , Goldgof D. B. 2006 Horizon Detection Using Machine Learning Techniques. International Conference on Machine Learning and Applications, 17-21.
- Gershikov E. , Libe T. , Kosolapov S. : Horizon Line Detection in Marine Images. 2013 Which Method to Choose? International Journal on Advances in Intelligent Systems, 6(1-2): 79 - 88.
- Gupta V. and Brennan S. 2008 Terrain Based Vehicle Orientation Estimation Combining Vision and Inertial Measurements. Journal of Field Robotics, 25(3):181 - 202.
- Ho N. and Chakravarty P. 2014 Localization on Freeways using the Horizon Line Signature. Proceedings of International Conference on Robotics and Automation (ICRA).
- Dumble S. J. and Gibbens P. 2014 Efficient Terrain-Aided Visual Horizon Based Attitude Estimation and Localization. Journal of Intelligent and Robotic Systems.
- Lie W. , Lin T. C. -I. , Lin T. , and Hung K. -S. . 2005 A robust dynamic programming algorithm to extract skyline in images for navigation, in Pattern Recognition Letters, 26(2) 221–230.
- Kim B. , Shin J. , Nam H. and Kim J. 2011 Skyline Extraction using a Multistage Edge Filtering World Academy of Science, Engineering and Technology.
- Haralick R. M. 1979 Statistical and structural approaches to texture, in: Proceedings of the IEEE, vol. 67, 786–804.
- Harlick R. M. , Shanmugam K. , Dinstein I. 1973 Textural Features for Image Classification. IEEE Trans, System. Man Cybernetic. 610–621.
- Barber D. G. , LeDrew E. F. 1991 SAR sea ice discrimination using texture statistics: a multivariate approach, Photogrammetric Engineering and Remote Sensing 57 (4) 385–395.
- Seber, G. A. F. 1984 Multivariate Observations. John Wiley & Sons, Inc. , Hoboken.
- Boyer M. , Tarjan, D. , Acton S. T. , Skadron K. 2009 Accelerating leukocyte tracking using CUDA: A case study in leveraging many core coprocessors," IEEE International Symposium on Parallel & Distributed Processing, 1–12.
- http://www. ee. unlv. edu/~yazdan/projects. html
- Pour Yazdanpanah A. , Regentova E. E. , Mandava A. K. , Ahmad T. , Bebis G. 2013 Sky Segmentation by Fusing Clustering with Neural Networks. 9th International Symposium on Visual Computing (ISVC), 663-672.
- Dhillon I. S. and Modha D. S. 2000 A data clustering algorithm on distributed memory multiprocessors. In Large-Scale Parallel Data Mining, Lecture Notes in Artificial Intelligence, 245–260.
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