The Ft. Carson data set [ 1 ], collected in a DARPA-sanctioned study, consists of about 150 color and IR images of camouflaged military vehicles under conditions that vary from bright (and hot) daytime to dark (and cool) dusk; the distance to the targets ranges from 100 to about 500 meters. The two independent systems (color and IR) were tested on corresponding images of 25 randomly chosen scenes from the Ft. Carson set.
The color-based system was applied by cross-validation, where half the images were used for training and the other half for testing (with rotation, so that all 25 images were used). In this test, 47 out of 50 targets were detected, with 39 false alarms. The false alarms were all due to background foliage which was very close in color to the camouflage of the vehicles; in two images with extremely poor lighting conditions the system missed the targets. In addition, the system was tested live at the UGV Demo-C, with similar results (the exact numbers from Demo-C are not available).
By comparison, the IR-based system [ 11 ] detected 22 of the 50 targets, with 5 false alarms. Four of the false alarms were from background foliage, and one was a civilian vehicle. Two issues must be noted, however: (a) the failure of the IR system can be attributed to the image quality - the fact that such images were collected in a realistic DARPA exercise goes to show that IR images cannot always be relied upon, even with sophisticated detection techniques; (b) when the color system failed due to poor lighting conditions, the IR system successfully detected the targets. When the two systems were combined, 100% of the targets were detected.
Shashi Buluswar