In comparison to present security applications, pattern recognition techniques can be categorized as 'hard' automatic target recognition (ATR) and 'soft' ATR. The first category has been established for years and deals with specific object recognition. On the other hand, the second, less established category operates on very fast object class-level recognition only. The second category usually employs very fast processing and an image database. In this paper, we introduce a novel method to integrate a compression technique based on logic data representation with soft ATR. This new compression method applies Arnold's Differential Mapping Singularities Theory in the context of 3D object projection into the 2D image plane, and takes advantage of the fact that object edges can be interpreted in terms of singularities, which can be described isomorphically by simple polynomials. Therefore, compared to state- of-the-art still image compression, such as JPEG, there is no information los in high contrast, high-dynamic range image areas; as a result, the global peak signal noise ratio can be very high By using linked edges to represent an object, it is possible to use a simple set of parameters for real-time 'soft' ATR. This publication discuses various security applications of this new scheme, which is integrated with ATR compression.