A new crater recognition method and its applications to images of Mars

Details A new crater recognition method and its applications to images of Mars A new crater recognition method and its applications to images of Mars

Apr 2003

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003eaeja.....8974a&link_type=abstract

EGS - AGU - EUG Joint Assembly, Abstracts from the meeting held in Nice, France, 6 - 11 April 2003, abstract #8974

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Scientific paper

Cratering is the dominant external geodynamic process on terrestrial planets. Crater counting is an essential step in planetary geologic studies, albeit a heavily time-consuming and manpower-consuming one. The present work introduces an automatic crater recognition method that compares favourably with other approaches, such as the circular Hough transform: it is less sensitive to noise, it is less memory-demanding and it is well suited to fast implementations that can be the base for autonomous landing guidance systems on very remote targets. The method is very simple, being based on classic image enhancement and recognition procedures: A. Image pre-processing. 1.Original greyscale image. 2.Stretch histogram between 0 and 256. 3.3x3 mean filter. 4.Detect edges with Sobel convolution. 5.Threshold at average + 2 standard deviations, producing a 2-bit image. B. Crater recognition (on 2-bit image). 1.Input Rmin, Rmax and Arc - minimum and maximum search radiuses, and circle arc to be considered a crater (between 1 and 2 PI). 2.R=Rmax. 3.x=x0; y=y0 4.Count all 1-pixels that are one radius away from (x, y). 5.If number of pixels is greater than Arc, then there is a crater of centre (x, y) and radius R. 6.Erase pixels on recognised crater (make every recognised 1-pixel a 0-pixel). 7.Increase centre coordinates until all pixels are covered. 8.Decrease R by one pixel until Rmin is reached. On all subsequent tests, Rmin=2 (pixel), Rmax=Image_side/4, [1.00PI

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