Camouflaged robots and leave-behind surveillance sensors are desirable in information, surveillance and reconnaissance operations to minimize the chances of detection by the enemy. Today's camouflaging techniques involve nets and painted patterns that are fixed in color and geometry, limiting their use to specific environments; a fact illustrated by numerous changes in military uniforms designed to fit the latest operating environment. Furthermore, nets are bulky and can interfere with the operation or use of a robot or leave-behind sensor. A more effective technique is to automatically adapt surface patterns and colors to match the environment, as is done by several species in nature. This can lead to the development of new and more effective robotic behaviors in surveillance missions and stealth operations. This biologically-inspired adaptive camouflage can be achieved by a) sampling the environment with a camera, b) synthesizing a camouflage image, and c) reproducing it on color electronic paper - a thin low-power reflective display - that is part of the outer enclosure surface of the robot or device. The focus of this paper is on the work performed for the first two steps of the process. Color-camouflage-synthesis is achieved via modifications made to a gray-level texturesynthesis method that makes use of gray-level co-occurrence matrices. Statistic equality in color-proportion is achieved with the use of conditional probability constraints.
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