Automatic target detection and recognition (ATD/R) is of crucial interest to the defense community. We present a robust ATD/R system developed at the CVRC at UT-Austin for recognition in second generation forward looking infrared (FLIR) images. An experiment conducted on 1,930 FLIR images shows that this ATR system can achieve recognition with a high degree of accuracy and a low false alarm rat...

In this paper, we present a novel synthesis of two separate areas of image processing: automatic target recognition/cueing (ATR/ATC) and embedded image compression. In order to maximize the information content of a transmitted image, an ATR algorithm is used to detect potential areas of interest, and the compression algorithm regionally compresses the image, allocating more bits to the areas of...

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...

| We present a performance analysis of an indexing module contained in an automatic target recognition (ATR) system developed at Worcester Polytechnic Institute (WPI). The Linear Signal Decomposi-tion/Direction of Arrival (LSD/DOA) technique provides a low computational-cost indexing function for pose in ATR applications. The LSD/DOA technique forms a reduced-size, essential-information object ...

In this paper we present a fuzzy system based hyperspectral classi®er for automatic target identi®cation. The system is based on partitioning the spectral band space into clusters using a modi®ed fuzzy C-Means clustering algorithm. Classi®cation of each pixel is then carried out by calculating its fuzzy membership in each cluster. The results showed that the fuzzy hyperspectral classi®er is suc...

This paper proposes an automatic target recognition (ATR) system based on the three-dimensional (3D) reconstruction of the target from an image sequence. The main contribution of this work is twofold: (1) we present a modi®ed voxel coloring reconstruction algorithm and (2) we employ the 3D reconstructed target model to generate the front and side target templates at zero depression angle to be ...

The task of identifying objects in images is a common requirement for many image processing systems. The identification of these objects (also called models) is in some contexts called automatic target recognition (ATR). Target Recognition algorithms are well suited to hardware field programmable gate array (FPGA) implementations because of their extensive use of bitlevel operations and their a...

In the field of automatic target recognition(ATR) with synthetic aperture radar(SAR) imagery, it is usually impractical to obtain SAR images covering a full range aspect views. When database consists limited angular diversity, can lead performance degradation SAR-ATR system. To address this problem, paper proposes deep learning-based method where channel attention modules(CAMs) are inserted con...

This effort advanced the art of applying Grenander's pattern theory to automatic target recognition (ATR) problems. We extended jump-diffusion ATR algorithms to accommodate unknown infrared camera calibration effects and include more stable diffusion procedures for pose refinement, and developed flexible shape models to accommodate clutter. We also developed performance bounds on estimation and...