SBOR – Similarity-based object retrieval: Computer simulations generate vast quantities of spatio-temporal output that can be challenging to explore using visualization alone. A display of an interesting region in one simulation may well prompt a scientist to ask if there were other similar regions in the same or in other simulations. We borrowed ideas from the field of content-based image retrieval (also called query by image content) to demonstrate that we could indeed address such questions, provided we carefully extracted the features representing the region of interest.

Select publications (available from Google Scholar):

  • S. Newsam and C. Kamath, “Comparing shape and texture features for pattern recognition in simulation data,” Image Processing: Algorithms and Systems IV, SPIE Electronic Imaging, January 2005.
  • Newsam, S. and C. Kamath, “Retrieval using texture features in high resolution multi-spectral satellite imagery,” Data Mining and Knowledge Discovery: Theory, Tools, and Technology, VI, SPIE Volume 5433, pp. 21-32, SPIE Defense and Security, Orlando, April 2004.
  • Cantu-Paz, E., Cheung, S-C., and Kamath, C., “Retrieval of Similar Objects in Simulation Data Using Machine Learning Techniques,” Image Processing: Algorithms and Systems III, SPIE Volume 5298, pp 251-258. SPIE Electronic Imaging, San Jose, January 2004.
  • Kamath, C., E. Cantu-Paz, S.-C. Cheung, I. K. Fodor, and N. Tang, “Experiences in mining data from computer simulations,” book chapter, New Generation of Data Mining Applications, IEEE Press, August 2003.

Validation of computer simulations: Validation is the process of checking how close a computer simulation is to reality, for example by comparing the simulation with experiments. Since the simulation output could be a two-dimensional unstructured grid, while the experimental data may be in the form of images, a direct comparison is not an option. Using the Richtmeyer-Meshkov instability as an example, we showed how we could extract features from both the simulation grid data and the noisy experimental images to validate the simulation.

Select publications (available from Google Scholar):

  • C. Kamath and P. L. Miller, “Image Analysis for Validation of Simulations of a Fluid Mix Problem,” IEEE International Conference on Image Processing, Volume III, pages 525-528, San Antonio, September 2007.
  • C. Kamath and T. Nguyen, “Feature Extraction from Simulations and Experiments: Preliminary Results Using a Fluid Mix Problem,” Technical report, Lawrence Livermore National Laboratory, UCRL-TR-208853, January 2005.