Open AccessAn Automatic Detection Algorithm for Small Craters Based on Morphology
Author(s) -
Sushuang Ma,
Jiarui Liang,
Xiaolin Tian
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1624/4/042014
Subject(s) - impact crater , astrobiology , geology , planet , lunar craters , remote sensing , mars exploration program , blank , martian , planetary surface , computer science , materials science , astrophysics , physics , composite material
Study of impact craters on planetary surfaces has revealed secrets of the evolution of planets. Identifying craters on planetary surfaces has become fundamental in planetary researches, whereas time-consuming, e.g. months to years to collect crater database. Small craters, including a large number of secondary craters, have shown its importance in researches of planetary sciences, whose database requires construction. Whereas, few studies concentrate on detection of small craters. In this paper, the writer adopts morphology-based algorithm to detect and localize the crater candidates effectively. The methodology has shown its effectiveness by detecting 869 small crater candidates in a region covering 37500 × 56250 m 2 on the Martian surface, with a precision of 79.29 %. Among those true positive detections, 91.25 % are craters with a diameter less than 1 km (not included). Compared with existing automatic detection methods on planetary impact craters, the method proposed in this paper performs better on detection of small craters, and it fills the blank of detection of craters with a diameter less than 200 m. Focusing on detection of small craters, it can provide a tool for quickly generating datasets for planetary scientific research in a targeted manner.