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A multi-sensor approach to buried object discrimination has been developed by Coleman Research Corporation (CRC) as a practical successor to currently prevalent metal detectors. The CRC multi-sensor unit integrates with and complements standard metal detectors to enable the detection of low-metallic and non-metallic anti-tank and anti-personnel mines as well as the older metallic-jacketed mines. The added sensors include Ground Penetration Radar (GPR) and Infrared (IR). The GPR consists of a lightweight (< 1 LB) snap on antenna unit, a belt attached electronics unit (< 5 LB) and batteries. The JR consists of a lightweight (<3 LB) head mounted camera, a heads-up virtual display, and a belt attached processing unit (Figure 1.1). The output from Automatic Target Recognition algorithms provide the detection of metallic and non-metallic mines in realtime on the JR display and as an audio alert from the GPR and MD.

Key words: Image processing, SIMD, GAPPTM, algorithm complexity, KhorosTMThe answer asked in the paper title is a resounding YES ! We are building automatic target recognizer (ATR) systems. These systems are being applied to many different target detection scenarios. Our work has been in the military application field, but the problems are the same for most commercial applications as well. The measures ofperformance are the same. How well can a human perform the same target detection task? What is the probability of detecting (Pd) the target versus the false alarm rate (FAR)? The community has evolved comparative performance techniques that present the merits of alternative system approaches. In this paper, we present the results of a comparative study of alternative algorithms for detecting and classifying buried and surface land mines from an airborne platform in infrared imagery. The results show that for low signalto-clutter ratios, more complex algorithms produce higher Pd for a given FAR. More complex algorithms signify the need for a high performance, high throughput processor to meet typical time lines. An update on the Geometric Arithmetic Parallel Processor (GAPPTM 1) high performance/throughput machine is therefore provided.