Abstract
In this paper, a novel method is proposed to extract rocks from Martian surface images by using data field. Data field is given to model the interaction between two pixels of a Mars image in the context of the characteristics of Mars images. First, foreground rocks are differed from background information by binarizing image on rough partitioning images. Second, foreground rocks is grouped into clusters by locating the centers and edges of clusters in data field via hierarchical grids. Third, the target rocks are discovered for the Mars Exploration Rover (MER) to keep healthy paths. The experiment with images taken by MER Spirit rover shows the proposed method is practical and potential.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Thompson, D.R., Castano, R.: Performance comparison of rock detection algorithms for autonomous planetary geology. In: Aerospace, IEEEAC Paper No. #1251. IEEE, USA (2007)
Wagstaff, K.L., et al.: Science-based region-of-interest image compression. In: 35th Lunar and Planetary Science Conference, League City, Texas, USA (2004)
Li, R., et al.: Rock modeling and matching for autonomous long-range Mars rover localization. Journal of Field Robotics 24(3), 187–203 (2007)
Gor, V., et al.: Autonomous rock detection for mars terrain. In: Space 2001. American Institute of Aeronautics and Astronautics, Albuquerque (2001)
Adelmann, H.G.: Butterworth equations for homomorphic filtering of images. Computers in Biology and Medicine 28(2), 169–181 (1998)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. International Journal of Computer Vision 1(4), 321–331 (1988)
Ji, L., Yan, H.: Attractable snakes based on the greedy algorithm for contour extraction. Pattern Recognition 35(4), 791–806 (2002)
Yuen, P.C., Feng, G.C., Zhou, J.P.: A contour detection method: initialization and contour model. Pattern Recognition Letters 20(2), 141–148 (1999)
Gulick, V.C., et al.: Autonomous image analyses during the 1999 Marsokhod rover field test. Journal of Geophysical Research 106(E4), 7745–7763 (2001)
Thompson, D.R., et al.: Data mining during rover traverse: from images to geologic signatures. In: 8th International Symposium on Artificial Intelligence, Robotics and Automation in Space, USA (2005)
Song, Y.H., Shan, J.: Automated rock segmentation for Mars Exploration Rover imagery. In: Lunar and Planetary Science Conference XXXIX, Houston, USA (2008)
Giachetta, G., Mangiarotti, L., Sardanashvily, G.: Advanced Classical Field Theory. World Scientific Publishing Co. Pte. Ltd (2009)
Wang, S.L., Gan, W.Y., Li, D.Y., Li, D.R.: Data Field for Hierarchical Clustering. International Journal of Data Warehousing and Mining 7(4), 43–63 (2011)
Li, D.R., Wang, S.L., Li, D.Y.: Spatial Data Mining theories and applications. Science Press, Beijing (2006)
Gonzalez, R.C., Woods, R.E.: Digital image processing, 3rd edn. Pearson Education, Upper Saddle River (2008)
Karypis, G., Han, E.H., Kumar, V.: Chameleon: Hierarchical Clustering Using Dynamic Modeling. Computer 32(8), 68–75 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, S., Chen, Y. (2011). Extracting Rocks from Mars Images with Data Fields. In: Tang, J., King, I., Chen, L., Wang, J. (eds) Advanced Data Mining and Applications. ADMA 2011. Lecture Notes in Computer Science(), vol 7120. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25853-4_28
Download citation
DOI: https://doi.org/10.1007/978-3-642-25853-4_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25852-7
Online ISBN: 978-3-642-25853-4
eBook Packages: Computer ScienceComputer Science (R0)