Abstract
Image analysis methods are commonly employed to determine the size and shape of particles. Although commercial and non-commercial tools enable detection and measurement of grains from images, they do not provide good results in the case of images acquired during extensive in situ Martian investigations. Within the confines of the Mars Exploration Rover (MER) mission and the Mars Science Laboratory (MSL) mission thousands of images of sand grains were captured, and hitherto, they are the only source of ground-truth data on Martian sand particles. Therefore, a new approach is proposed to analyze such images. The semi-automatic algorithm allows fast detection and measurement of the size and shape of Martian grains from images obtained by the Microscopic Imager (MI) and the Mars Hand Lens Imager (MAHLI). The method was evaluated on 76 images of terrestrial and Martian deposits. The results for the terrestrial samples were compared to those from sieve analysis, as well as with ImageJ and Malvern Morphologi G3 systems. The method provides similar results to those from the other methods. It does not have any limitation on the size of grains, and permits separation of touching particles.
Highlights
Aeolian processes play a significant role in shaping the present surface of Mars
The circularity was calculated as: 4πA/P2, where: A is the area of a particle, and P is the perimeter of a particle
The comparisons of the morphological parameters and cumulative size frequency distributions for the images of the terrestrial samples computed by Morphologi G3 system and PADM algorithm are presented in Table 2 and Fig. 8
Summary
Aeolian processes play a significant role in shaping the present surface of Mars. To obtain information on aeolian transport we need to bring together data about aeolian bedforms and the materials that they are composed of. The method uses a series of morphological opening or closing operations, and it provides only some information on the size of grains passing through the given structuring element. This technique does not allow studying the shape of grains. To obtain information on morphological parameters of individual particles, an image segmentation technique, enabling the detection of grain boundaries, must be applied (Fu and Mui 1981). This approach often allows the separation of overlapping or touching grains. Accuracy Structuring Binarization Edge detection Sharpening Gradient element range threshold range range filter range
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