Research Survey of Passive Image-Based Impact Crater Detection
DING Meng1, LI Haibo2, CAO Yunfeng3, ZHUANG Likui3
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1. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China 2. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China 3. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
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Received
Revised
Published
15 Dec 2014
14 Apr 2015
20 May 2022
Issue Date
20 May 2022
Abstract
Currently more and more technologies of information science, such as image processing and pattern recognition, are used in the development of space science. The autonomous crater detection which gains many researchers'attention in recent years is one of the good examples in this field. This paper introduces the autonomous crater detection technology from passive images in details. Firstly, the applications of autonomous crater detection in three areas including geology or astronomy, space database establishment and spacecraft navigation and positioning are discussed. Secondly, the state of autonomous crater detection technology is introduced, esp. some typical algorithms are addressed. In order to explain these methods clearly, the related algorithms are classified into three kinds: Unsupervised Detection, Supervised Detection and Combination Detection. Finally, the difficulties, further work of autonomous crater detection and the author's work are addressed shortly.
DING Meng, LI Haibo, CAO Yunfeng, ZHUANG Likui.
Research Survey of Passive Image-Based Impact Crater Detection. Journal of Deep Space Exploration, 2015, 2(3): 195‒202 https://doi.org/10.15982/j.issn.2095-7777.2015.03.001
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References
[1] 张玥,李清毅,许晓霞.月球表面地形数学建模方法[J].航天器环境工程,2007,24(6):341-343. [Zhang Y, Li Q Y, Xu X X. The mathematical modeling approach of lunar surface terrain[J]. Spacecraft Environment Engineering, 2007,24(6):341-343.] [2] 邓剑.月球探测器软着陆过程中的障碍识别[D].吉林大学, 2007.[Deng J. Lunar obstacle detection in the process of lunar lander's landing[D]. Jilin University, 2007.] [3] 郭烈,王荣本,毛晓燕,等.基于机器视觉的环境感知坑检测方法研究[C]//中国宇航学会深空探测技术专业委员会第二届学术会议论文集.北京:CDSET. 2005,12(16):143-144. [Guo L, Wang R B, Mao X Y, et al.CDSET-CSA the second academic conference proceedings[C]//The 2th CDSET papers, Beijng: CDSET. 2005,12(16):143-144.] [4] Tanaka K L. The stratigraphy of Mars[J]. Journal of Geophysical Research, 1986,91(30):E139-E158. [5] Neukum G, Konig B, Arkani-Hamed J. A study of lunar impact crater size-distributions[J]. Earth, Moon, and Planets, 1975,12(2):201-229. [6] Soderblom L A, Condit C D, West R A, et al. Martian planetwide crater distributions: implications for geologic history and surface processes[J]. Icarus, 1974,22(3):239-263. [7] Cintala M J, Mouginis-Mark P J. Martian fresh crater depth: more evidence for subsurface volatiles[J]. Geophysical Research Letters, 1980(7):329-332. [8] Rodionova J F, Dekchtyareva K I, Khramchikhin A A, et al. Morphological catalogue of the craters of Mars[M]. Noordwijk, The Netherlands: ESA-ESTEC, 2000. [9] Barlow N G. Revision of the "catalog of large martian impact craters[C]//Sixth International Conference on Mars. [S.l.]:[s.n.], 2003. [10] Barlow N G. Crater size-distributions and a revised martian relative chronology[J]. Icarus, 1988,75(2):285-305. [11] Yang C, et al. The Mars exploration rovers descent image motion estimation system[J]. IEEE Intelligent Systems, 2004(3):13-21. [12] Cheng Y, Johnson A E, Matthies L H, et al. Optical landmark detection for spacecraft navigation[C]//in Proc of the 13th AAS/AIAA Space Flight Mechanics Meeting, Ponce, Puerto Rico. [S.l.]: AIAA,2003:1785-1803, AAS 03-224. [13] Cheng Y. Autonomous landmark based spacecraft navigation system[C]//AAS/AIAA Space Flight Mechanics Meeting. Ponce: AIAA, 2003. [14] NASA. Autonomous landing and hazard avoidance technology[EB/OL]. http://www-robotics.jpl.nasa.gov/tasks/showTask.cfm?FuseAction=showTask&TaskID=84&tdaID=999986. [15] Huertas A. Passive imaging based multi-cue hazard detection for spacecraft safe landing[C]//2006 IEEE Aerospace Conference. [S.l.]: IEEE, 2006. [16] Cheng Y, Johnson A E, et al. Passive imaging based hazard detection for spacecraft safe landing[C]//2000 IEEE Aerospace Conference. [S.l.]:IEEE, 2000. [17] Leroy B, Medioni G, Johnson A E, et al. Crater detection for autonomous landing on asteroids[J]. Image Vis. Comput., 2001,19( 11) :787-792. [18] Honda R, Iijima Y, Konishi O. Mining of topographic feature from heterogeneous imagery and its application to lunar craters[C]//In Progress in Discovery Science: Final Report of the Japanese Discovery Science Project. New York: Springer-Verlag, 2002. [19] Bandeira L, Saraiva J, Pina P. Enhancing impact crater rims to increase recognition rates, in Proc[C].//VISAPP-1st Int. Conf. Computer Vision Theory Applications. Portugal:[s.n.], 2006:407-412. [20] Bandeira L, Saraiva J, Pina P. Impact crater recognition on Mars based on a probability volume created by template matching[J]. Geoscience and Remote Sensing, IEEE Transactions on, 2007,45(12):4008-4015. [21] Barata T, Ivo Alves E, Saraiva J, et al. Automatic recognition of impact craters on the surface of mars[C]//In Proc. ICIAR. Porto,Portugal:[s.n.], 2004:489-496. [22] Kim J R, Muller J P, Morley J G. Quantitative assessment of automated crater detection on Mars[C]// In Proc. 20th ISPRS Congr.. Istanbul, Turkey:[s.n.], 2004:816-821. [23] Kim J R., Muller J P, Gasselt S V, et al. Automated crater detection, a new tool for Mars cartography and chronology[J]. Photogramm. Eng. Remote Sens, 2005,71(10):1205-1217. [24] Bue B D, Stepinski T F. Machine detection of martian impact craters from digital topography data[J]. IEEE Trans. Geosci. Remote Sens, 2007,45(1):265-274. [25] Honda R, Azuma R. Crater extraction and classification system for lunar images[J]. Mem. Fac. Sci. Kochi Univ. (Inform. Sci.), 2000(21):13-22. [26] Jahn H. Crater detection by linear filters representing the Hough transform[C]//In Proc. SPIE—ISPRS Commission III Symp.: Spatial Information from Digital Photogrammetry Computer Vision. Munich:[s.n.], 1994(2357):427-431. [27] Vinogradova T, Burl M, Mjolness E. Training of a crater detection algorithm for Mars crater imagery[C]//In Proc. IEEE Aerosp. Conf., Big Sky, MT:[s.n.], 2002(7):3201-3211. [28] Matsumoto N, Asada N, Demura H. Automatic crater recognition on digital terrain model[C]//In Proc. Lunar Planetary Sci. XXXVI. Houston:[s.n.], 2005. [29] Homma K, Yamamoto H, Isobe T, et al. Massively parallel processing for crater recognition[C]//In Proc. Lunar Planetary Sci. XXVIII.Houston:[s.n.],1997. [30] Flores-Méndez A. Crater marking and classification using computer vision[C]//In Progress in Pattern Recognition, Speech and Image Analysis, vol. 2905, Lecture Notes in Computer Science. New York: Springer-Verlag, 2003:79-86. [31] Michael G.Coordinate registration by automated crater recognition[J]. Planetary Space Sci, 2003,51(9):563-568. [32] Bandeira L P C, Saraiva J, Pina P. Development of a methodology for automated crater detection on planetary images[M]. Pattern recognition and image analysis. Germany: Springer Berlin Heidelberg, 2007. [33] Magee M. Automated identification of martain craters using image processing[M]. LPSCXXXIV, 2003. [34] Saraiva. A structured approach to automated crater detection[M]. LPSCXXXVII,2006. [35] Brumby S, Plesko C, Asphaug E. Evolving automated feature extraction algorithms for planetary science[C]//Proc. ISPRS WG IV/9: Extraterrestrial Mapping Workshop-Advances Planetary Mapping. Houston:[s.n.], 2003. [36] Plesko C, Werner S, Brumby S E, et al. A statistical analysis of automated crater counts in MOC and HRSC data[C]//Proc. Lunar Planetary Sci. XXXVII. Houston:[s.n.], 2006. [37] Hough P V C. Method and means for recognizing complex patterns: U.S., 3 069 654[P]. 1962-12-18. [38] Olson C F. Improving the generalized Hough transform through imperfect grouping[J]. Image and Vision Computing, 1998,16(9):627-634. [39] Olson. Decomposition of the hough transform: curve detection with efficient erorpropagation[C]//Proceedings of the European conference on Computer Vision, [S.l.]:[s.n.],1996. [40] Xu L, Oja E, Kultaned P. A new curve detection method: Randomized Hough Transform(RHT)[J]. Pattern Recognition Letter, 1990,11(5):331-338. [41] Honda. Data mining system for planetary images-crater detection and categorization[J].http://citeseer.ist.psu.edu/436870.html. [42] Johnson A E, Klump A. LIDAR-base hazard avoidance for safe landing on Mars[C]//AAS/AIAA Space Flight Mechanics Meeting. Santa Barbara: AIAA, 2001. [43] Johnson A E. Surface landmark selection and matching in natural terrain[C]//Proc. IEEE Computer Vision and Pattern Recognition. [S.l.]: IEEE, 2000. [44] 杨忠根,马彦.使用广义正交概念的 K—RANSAC椭圆提取[J].自动化学报,2002,28(4):520-526.[Yang Z G, Ma Y. A new method for ellipse detection using K-RANSAC based on generalized orthogonality principle[J]. Acta Automatica Sinica, 2002,28(4):520-526.] [45] Nagase T, Agui T, Nagahashi H. Pattern matching of binary shapes using a genetic algorithm[J]. Transaction of IEICE, 1993,J76-D-II(3):557-565. [46] Watanabe T, Shibata T. Detection of broken ellipse by the Hough Transforms and multi-resolutionalImages[J]. Transaction of IEICE, 1990, J83-D-2(2):159-166. [47] Kohonen T. Self-organizing maps, 2nd eds[M]. Germany:Springer,1997. [48] Burl M C, Stough T, Colwell W, et al. Automated detection of craters and other geological features[C]//In Proc. Int. Symp. Artif. Intell., Robot. andAutom. Space, Montreal, QC. Canada:[s.n.], 2001. [49] 陈建清, 朱圣英, 崔祜涛, 等. 应用灰度特征的行星陨石坑自主检测方法与着陆导航研究[J]. 宇航学报, 2014, 35(8): 908-915.[Chen J Q, Zhu S Y, Cui H T, et al. Automated crater detection method using gray value features and Planet landing navigation research[J]. Journal of Astronautics, 2014,35(8):908-915.] [50] Vinogradova T, Burl M, Mjosness E. Training of a crater detection algorithm for Mars crater imagery[C]//In Proc. IEEE Aerosp. Conf. [S.l.]: IEEE, 2002. [51] Wetzler P G, Enke B, Merline W J, et al. Learning to detect small impact craters[C]//In Proc. 7th IEEEWACV/MOTION. [S.l]:[s.n.], 2005. [52] Smirnov A. Exploratory study of automated crater detection algorithm, dept. of computer science, university of colorado[R]. Internal Report, www. cs. colorado. edu/rossnd/fcdmf/CraterPaper. pdf, 2002. [53] 岳宗玉,刘建忠,吴淦国.应用面向对象分类方法对月球撞击坑进行自动识别[J].科学通报,2008,53(22):2809-2813. [Yue Z Y, Liu J Z, WU G G. Automatic identification to lunar impact crater using object-oriented sorting technique[J]. Science, 2008,53(22):2809-2813.] [54] Sawabe Y, Matsunaga T, Rokugawa S. Automated detection and classification of lunar craters using multiple approaches[J]. Adv. Space Res., 2006,37(1):21-27. [55] Magee M, Chapman C R, Dellenback S W, et al. Automated identification of Martian craters using image processing[C]//34th Lunar and Planetary Science Conference; Abstracts of Papers. [S.l.]:[s.n.], 2003. [56] Earl J, Chicarro A F, Koeberl C, et al. Automatic recognition of crater-like structures in terrestrial and planetary images[C]//In Proc. Lunar Planetary Sci. XXXVI. Houston:[s.n.], 2005. [57] Bandeira L, Saraiva J, Pina P. Development of a methodology for automated crater detection on planetary images[C]//In Proc.Iberian Conf. Pattern Recog. Image Anal. [S.l.]:[s.n.], 2007. [58] 张锋,邹永廖,郑永春,等.月表撞击坑自动识别与提取的新方法及其应用[J].地学前缘,2012,19(006):118-127.[Zhang F, Zou Y L, Zheng Y C, et al.A new automated approach to detecting and extracting lunar craters and its application[J]. Earth Science Frontiers, 2012,19(6):118-127.] [59] 罗中飞,康志忠,刘心怡.融合嫦娥一号CCD影像与DEM数据的月球撞击坑自动提取和识别[J].测绘学报,2014,43(9):924-930. [Luo Z F, Kang Z Z, Liu X Y. The automatic extraction and recognition of lunar impact craters fusing CCD[J]. Acta Geodaetica et Cartographica Sinica, 2014,43(9):924-930.] [60] Ding M, Cao Y F, Wu Q X. Autonomous craters detection from digital image[C]//The 3th International Conference On Innovation Computing, Intelligence and Contro. [S.l.]:[s.n.], 2008.
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