ISPRS 2003 Evolving Automated Feature Extraction Algorithms for Planetary Science

Planetary exploration missions have returned a wealth of imagery data over the last 40 years. The problem is how to make best use of it all. Thoroughly analyzing such large datasets manually is impractical, but developing handwritten feature extraction software is difficult and expensive. The current project explores the use of machine learning techniques to automate the development of feature extraction algorithms for the Mars Orbiter Camera (MOC) narrow angle dataset using Los Alamos National Laboratory’s GENIE machine learning software. GENIE uses a genetic algorithm to assemble feature extraction algorithms from low-level spatial and spectral image processing steps. Each algorithm is evaluated against user-provided training data, and the most accurate ones are allowed to "reproduce" to build new solutions. The result is automated feature extraction algorithms customized to the dataset at hand and the current feature of interest. A graphical user interface is used to provide training data, allowing map-makers without programming experience the ability to generate new feature extraction algorithms.

Mimetype

application/pdf

Filename

Brumby_isprs_mar03.pdf

Publisher

ISPRS

Originator

S. P. Brumby, C. S. Plesko, E. Asphaug

Group

Astrogeology

Added to Astropedia

14 May 2012

Modified

9 July 2013

General

Geospatial Data Presentation Form

Document

Keywords

System

Target

Theme

Image Processing

Geospatial Information

Quad Name