Genie Pro: robust image classification using shape, texture, and spectral information

Simon Perkins; Kim Edlund; Diana Esch-Mosher; Damian Eads; Neal Harvey; Steven Brumby

doi:10.1117/12.604519

1 June 2005 Genie Pro: robust image classification using shape, texture, and spectral information

Simon Perkins, Kim Edlund, Diana Esch-Mosher, Damian Eads, Neal Harvey, Steven Brumby

Proceedings Volume 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI; (2005) https://doi.org/10.1117/12.604519
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

We present Genie Pro, a new software tool for image analysis produced by the ISIS (Intelligent Search in Images and Signals) group at Los Alamos National Laboratory. Like the earlier GENIE tool produced by the same group, Genie Pro is a general purpose adaptive tool that derives automatic pixel classification algorithms for satellite/aerial imagery, from training input provided by a human expert. Genie Pro is a complete rewrite of our earlier work that incorporates many new ideas and concepts. In particular, the new software integrates spectral information; and spatial cues such as texture, local morphology and large-scale shape information; in a much more sophisticated way. In addition, attention has been paid to how the human expert interacts with the software: Genie Pro facilitates highly efficient training through an interactive and iterative “training dialog”. Finally, the new software runs on both Linux and Windows platforms, increasing its versatility. We give detailed descriptions of the new techniques and ideas in Genie Pro, and summarize the results of a recent evaluation of the software.

Citation Download Citation

Simon Perkins, Kim Edlund, Diana Esch-Mosher, Damian Eads, Neal Harvey, and Steven Brumby "Genie Pro: robust image classification using shape, texture, and spectral information", Proc. SPIE 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, (1 June 2005); https://doi.org/10.1117/12.604519

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