Automatic image processing technique to detect the surface variations of planet Mars (original) (raw)
The goal of this project is to develop a methodology for classification and characterization of topographical features of Mars and to detect the variations of Martian surface features by designing an automated geomorphic mapping method for planet Mars. Mars has bright polar caps which make dramatic changes with the seasons. In the winter season for a pole, the cap becomes much larger as carbon dioxide freezes on the surface (dry ice). The cap gradually increases in size by the beginning of spring. Hence this study was focused on developing a good technique which can identify and analyze the Ice caps automatically. In addition Special attention was given to develop a method to identify new meteoroid hits on the Mars surface because craters were very important feature of a planet surface. Images and their data were obtained from various international sources such as NASA within the time frame January 2009 to January 2014. Sensors were Mars Orbiter Camera (MOC), Mars Orbiter Laser Altimeter (MOLA) and ESA Mars Express (MEX). There were many surface variations in the Mars which change gradually. So an automated surface variation detection algorithm is developed which exploits image data. The study focused on analysing a set of areas which was identified by a researches conducted by NASA which used different methodologies. For all practical identification purposes of these images, a Graphical User Interface (GUI) was developed using MATLAB comprising of various shape detection utilities which facilitate crater detection, icecap detection and comparing images to find out surface variations. This study was able to validate the finding of the parallel research conducted at NASA with a crater detecting accuracy of 75%, 80% and 70% for large, medium and small size craters respectively. For surface variation detection, the accuracy of the developed system is 70%. The technique developed can be used very easily on Martian surface exploration studies in the fields such as cartography, geology, physics, and astronomy.
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