Improved automatic impact crater detection on Mars based on morphological image processing and template matching

Autor(es)

Pedrosa, Miriam Maria ^[1] ; de Azevedo, Samara Calcado ^[1] ; da Silva, Erivaldo Antonio ^[1] ; Dias, Mauricio Araujo ^[2]

Afiliação do(s) autor(es)

^[1] Sao Paulo State Univ, Dept Cartog, Presidente Prudente - Brazil

^[2] Sao Paulo State Univ, Dept Math & Comp Sci, Presidente Prudente - Brazil

• Tipo de documento: Artigo Científico
• Fonte: GEOMATICS NATURAL HAZARDS & RISK; v. 8, n. 2, p. 1306-1319, 2017.
• Citações Web of Science: 1

Resumo

Impact craters help scientists to understand the geological history of planetary bodies. The aim of this paper is to improve the existing methodology for impact craters detection in images of planetary surfaces using a new approach based on morphological image processing (MIP). The improved methodology uses MIP followed by template matching based on fast Fourier transform (FFT). In this phase, a probability volume is generated based on the correlation between templates and images. The analysis of this probability volume allows the detection of different size of impact craters. We have applied the improved methodology to detect impact craters in a set of images from Thermal Emission Imaging System onboard the 2001 Mars Odyssey Space probe. The improved methodology has achieved a crater detection rate of 92.23% which can be considered robust, since results were obtained based on geomorphological features, different illumination conditions and low spatial resolution. The achieved results proved the viability of using MIP and template matching by FFT, to detect impact craters from planetary surfaces. (AU)

• Processo FAPESP: 15/26743-5 - Detecção automática de sombras e remoção dos efeitos em imagens digitais de alta resolução espacial
• Beneficiário: Samara Calçado de Azevedo
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Doutorado
• Processo FAPESP: 13/25257-4 - Detecção automática de sombras e remoção dos seus efeitos em imagens digitais de alta resolução espacial
• Beneficiário: Samara Calçado de Azevedo
• Modalidade de apoio: Bolsas no Brasil - Doutorado