A fundamental problem facing the designers of automatic target recognition (ATR) systems is how to deal with out-of-library or non-registered targets. This research extends a mathematical programming framework that selects the optimal classifier ensemble and fusion method across multiple decision thresholds subject to classifier performance constraints. The extended formulation includes treatme...

Traditional methods for ATR (Automatic Target Recognition) use infrared (IR) sensors for detecting heat emanating from targets. IR-based ATR techniques are susceptible to sensor-induced errors; for instance, targets may not be detected if they are cold (when vehicle engines are turned o ), or when the background is hot (on a hot day). This work presents an approach to real-time color-based ATR ...

Laser Vibrometry is an exciting new sensor technology that promises to improve automatic target recognition (ATR) performance. Sensors such as Micro-Laser Interferometer Doppler (MLID) measure minute vibrations on the surface of an object from a large standoff distance. In this paper, we demonstrate a baseline ATR algorithm designed for vibrometry data that can reliably recognize military vehic...

A new algorithm is presented for Automatic Target Recognition (ATR) where the templates are obtained via Singular Value Decomposition (SVD) of High Range Resolution (HRR) profiles. SVD analysis of a large class of HRR data reveals that the Range-space eigenvectors corresponding to the largest singular value accounts for more than 90% of target energy. Hence, it is proposed that the Range-space ...

Automatic Target Recognition (ATR) is a demanding application that requires separation of targets from a noisy background in a sequence of images. In this paper, two adaptive methods for describing such a background are proposed which are based on Principal and Independent Component Analysis of sampled image patches. Coupled together with feature selection and outlier detection techniques they ...

Recent research in the calculation and exploitation of geometric object/image relations suggests new approaches to automatic target recognition (ATR). The resulting conceptual advances have efficiently solved the geometry problem and have transformed the ATR problem into a correspondence problem. This paper provides an analysis of the elementary algorithms which exploit object/image relations a...

Recognition of occluded objects in synthetic aperture radar (SAR) images is a signi0cant problem for automatic target recognition. Stochastic models provide some attractive features for pattern matching and recognition under partial occlusion and noise. In this paper, we present a hidden Markov modeling based approach for recognizing objects in SAR images. We identify the peculiar characteristi...

There is a large class of problems that are at best poorly solved. These problems involve the transformation of data across the boundary between the real world and the digital world. And they occur whenever a computer is sampling and/or acting on real world data. Examples of these “boundary transformation” problems include the computer recognition of human speech, computer vision, textual and i...

Automatic facial recognition has many potential applications in different areas of humancomputer interaction. However, they are not yet fully realized due to the lack of an effectivefacial feature descriptor. In this paper, we present a new appearance based feature descriptor,the local directional pattern (LDP), to represent facial geometry and analyze its performance inrecognition. An LDP feat...

Although a number of object recognition techniques have been developed to process LADAR scanned terrain scenes, these techniques have had limited success in target discrimination in part due to low-resolution data and limits in available computation power. We present a pose-independent Automatic Target Detection and Recognition System that uses data from an airborne 3D imaging Ladar sensor. The...