Automatic detection and characterization of Lunar Wrinkle ridges

Related computational advances, across various geoscience disciplines, have led to development of an upcoming field: Computers & Geosciences. This multidisciplinary research area is attracting interest of both computer science and planetary/space scientists since last two decades. Under this domain, the most significant area which is gaining importance is application of computational intelligence to automatically extract landforms present on planetary surfaces and determine their morphometric attributes. Wrinkle ridges are one of the common features on lunar surface that need to be explored more for further computation and analysis. This paper focuses on application of image processing approaches for automatic detection of wrinkle ridges and evaluation of morphometric parameters like length, width, orientation and area. The software developed was tested on DEMs (Data Elevation Model) of lunar wrinkle ridges utilizing SLDEM (Selene Lunar Data Elevation Model) data set. The test dataset comprises of 9 lunar wrinkle ridges having 62 segments with a total length of 1414 km. The results were verified by manual calculations using QGIS software. The software was found to perform with a mean percentage deviation varying from 3.10 to 5.97 for different parameters