Convexity-Based Visual Camouflage Breaking

Camouflage is frequently used by animals and humans (usually for military purposes) in order to conceal objects from visual surveillance or inspection. Most camouflage methods are based on superpositioning multiple edges on the object that is supposed to be hidden, such that its familiar contours and texture are masked. In this work, we present an operator, (Darg), that is applied directly to the intensity image in order to detect 3D smooth convex (or equivalently: concave) objects. The operator maximally responds to a local intensity configuration that corresponds to curved 3D objects, and thus, is used to detect curved objects on a relatively flat background , regardless of image edges, contours and texture. In that regard, we show that a typical camouflage found in some animal species, seems to be a " counter measure " taken against detection that might be based on our method. Detection by Darg is shown to be very robust, from both theo-retic considerations and practical examples of real-life images. As a part of the camouflage breaking demonstration, Darg, which is non-edge-based, is compared with a representative edge-based operator. Better performance is maintained by Darg for both animal and military camouflage breaking. 3 1. INTRODUCTION " Camouflage is an attempt to obscure the signature of a target and also to match its background " [1]. The goal of this paper is to detect 3D convex or concave objects under strong camouflage. We suggest an operator (" D arg "), which is applied directly to the intensity function. D arg maximally responds to the typical intensity signatures of smooth 3D convex or concave patches in the objects. The operator is not limited to any particular light source or reflectance function, as a large range of examples demonstrate. D arg implicitly takes advantage of the 3D structure of objects, but does not attempt to restore the three dimensional scene. Although prior knowledge or experience may aid one in breaking camouflage (e.g. [2]), our operator is context-free; its only a priori assumption about the target is its being three dimensional and convex (or concave). The purpose of D arg is detection of convex or concave subjects under harsh camouflage conditions or in highly cluttered scenes. D arg is robust to changes in illumination, scale, and orientation. The invariance theorem underlying the theoretic explanation for this phenomenon (proof supplied) is accompanied by real-life images. The theorem states that D arg is …