Cost-effective and promising approach for camouflage-assessment of MUSTAFA'S targets in motion-imagery

摘要

The camouflage assessment tool LOAT was introduced to the Austrian Air Reconnaissance Center at the end of 1999. This segmentation based and texture oriented method was already presented at AeroSense Conferences. For the new task of assessing video sequences of dynamic scenes this still-image method showed to be too time consuming - a different approach relying on former experiences seemed to be feasible. In June 2002 the three nations (Austria, Germany and Switzerland) camouflage-field-campaign "MUSTAFA" was conducted on Austria's largest proving-ground; data was recorded for the following expert analysis of the participants. Motion imagery was recorded in visual and thermal infrared bands. The scenario was the approach of an attack-helicopter towards typical military targets in use which were camouflaged with multi spectral measures. Besides a validation of the LOAT-System by selecting a small sample of the collected video frames a so called "video base analysis method" was developed and is scheduled for examining the MUSTAFA-videos for motion-camouflage-assessment. The "video base analysis method" (it will become LOMAT-system = low observables motion assessment tool if successful) is based on a very fast video-processing software. The assessment algorithm to be implemented is based on a MDL clustering algorithm in conjunction with a database for numerical inter frame analysis. Features are the results of the clustering process like information content of the data, number of classes found and the like. We consider it a very promising approach for the projected real-time task mainly because there is no calibration process involved. The research done by D2K Solutions Ruppert & Partner OEG, an Austrian spin-off company of Joanneum Research is scheduled to provide the basic tool at end of the second quarter of 2003; the examination of the MUSTAFA data is due until May 2003. The approach of the "video base-analysis method', the introduction of the MDL based assessment method will be presented together with preliminary visualizations e.g. screenshots of the work done so far. Samples of the collected motion-image will also be presented.