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检索条件"任意字段=Infrared Technology for Target Detection and Classification 1981"

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target classification algorithms for video and forward looking infrared (FLIR) imagery

Target classification algorithms for video and forward looki...

引用

infrared technology for target detection and classification 1981

作者： Yin, Barbara H. Mack, Harold Ford Aerospace and Communications Corporation Aeronutronic Division Ford Road Newport BeachCA92660 United States

The purpose of the target classification algorithms is to properly categorize the object isolated by the target detection and extraction algorithms. Feature determination and object classification with the given features are the two distinct phases associated with target classification. This paper compares the impact of using "radial and angular moments" versus Hu's seven Cartesian moment invariants, and also compares silhouette moments and intensity moments for feature extraction. The k-nearest neighbor approach is then used for the object classification phase. The efficacy of the technique has been evaluated off-line via the method of confusion matrices. The theoretical results are presented, supported by validation on the synthetic data base generated in our Digital Image Processing Lab. © 1982 SPIE. All rights reserved.

关键词： Extraction

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Eliminating nearest neighbor searches in estimating target orientation

Eliminating nearest neighbor searches in estimating target o...

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infrared technology for target detection and classification 1981

作者： Smithgall, Brian Image Processing Laboratory Hughes Aircraft Co. Bldg. 6/E147 Centinela and Teale Sts. Culver CityCA90230 United States

Frequently in image processing an unknown image is identified by matching features from the image to features of known images. One method of doing this is to compute a distance measure between the features of the two images. This measure indicates the dissimilarity between the images. This distance measure is computed for each of a large set of different known images. The process of exhaustively locating the known image with the minimum distance, and therefore the best match is called nearest neighbor matching.

关键词： target detection infrared technology Image processing Data storage Error analysis Distance measurement Electroluminescence Quantization Image classification Missiles

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Comparative study of edge-thinning algorithms for target identification

Comparative study of edge-thinning algorithms for target ide...

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infrared technology for target detection and classification 1981

作者： Kesh, H. Keshavan, R. Lo, Chun Moo Northrop Corporation Electro-Mechanical Division 500 East Orangethorpe Avenue AnaheimCA92801 United States

The aim of the edge thinning process is to remove the inherent edge broadness in gradient images while retaining edge continuity of the image. Such a process is required so that a useful silhouette of the target can be generated for target classification purposes. This paper compares the results from three candidate edge thinning algorithms: nonmaximum suppression technique by D. Miligram and A. Rosenfeld, modified USC thinning algorithm, and Reeves' algorithm. The results are compared subjectively and in terms of the number of computations required for their implementation. © 1982 SPIE. All rights reserved.

关键词： Optical engineering

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infrared ship classification using a new moment pattern recognition concept

Infrared ship classification using a new moment pattern reco...

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infrared technology for target detection and classification 1981

作者： Casasent, David Pauly, John Fetterly, Donald Carnegie-Mellon University Department of Electrical Engineering PittsburghPA15213 United States General Dynamics Pomona Division PomonaCA91769 United States

An analysis of the statistics of the moments and the conventional invariant moments shows that the variance of the latter become quite large as the order of the moments and the degree of invariance increases. Moreso, the need to whiten the error volume increases with the order and degree, but so does the computational load associated with computing the whitening operator. We thus advance a new estimation approach to the use of moments in pattern recognition that overcomes these problems. This work is supported by experimental verification and demonstration on an infrared ship pattern recognition problem. The computational load associated with our new algorithm is also shown to be very low. © 1982 SPIE. All rights reserved.

关键词： Ships

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Optimal performance limits for detection and classification algorithms

Optimal performance limits for detection and classification ...

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infrared technology for target detection and classification 1981

作者： Barlow, Carl A. Stern, Martin New Products Development Department Texas Instruments Incorporated Mail Station 3407 P.O. Box 405 LewisvilleTX75067 United States

A system which accepts a two-dimensional scene as input and produces an image of the scene as output introduces degradations to the image which cause a loss of information about the original scene. A mathematical model is described which, under certain assumptions about the scene, the transformations and the noise sources, models the effects of these degradations on the original scene and on the ability of any algorithm to classify objects in the scene. Three possible applications of this theory are (1) establishing whether a classification problem is supported by sufficient sensor data to admit a solution (2) determining which noise or system functions are most limiting and (3) providing an upper-bound performance against which suboptimal algorithms may be compared so as to establish the potential benefit which could result from algorithm improvements. © 1982 SPIE. All rights reserved.

关键词： Mathematical transformations

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Feature analysis for forward looking infrared (FLIR) target identification

Feature analysis for forward looking infrared (FLIR) target ...

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infrared technology for target detection and classification 1981

作者： Lin, Yun-Kung J. Government Communications Systems Division Harris Corporation Mail Stop 12-320 P.O. Box 37 MelbourneFL32901 United States

Feature analysis and classifier design toward real-time FLIR target identification are presented. After tarqet candidates of military vehicles are segmented in a low resolution FLIR scenario,1 a set of 17 features is extracted from these target areas in a single pass. These features consist of two optical intensity features, nine geometry features as well as six texture features. Five types of target candidates are examined in this study. They are tanks, APC's, jeeps, burning hulks, and other nontargets such as noise regions. A simple tree classifier is designed that is based on the manual interpretation of feature distribution among target categories at each nonterminal node of the tree classifier. The approach of feature extraction and classifier design has been applied to FLIR imagery provided by the U.S. Army Night Vision Laboratory and has shown promising results. © 1982 SPIE. All rights reserved.

关键词： Military vehicles

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Comparison of imaging infrared detection algorithms

Comparison of imaging infrared detection algorithms

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infrared technology for target detection and classification 1981

作者： Burton, Mark Benning, Carl Image Processing Systems Department Equipment Group Texas Instruments Incorporated M.S. 3407 P.O. Box 405 LewisvilleTX75067 United States

This paper compares the performance of four candidate target detection algorithms. The best known of these, "Superslice," was developed at the University of Maryland in 1977-78.1 The other three algorithms are the "Spoke Filter" developed by the Army Missile Command in Huntsville;2,3 the "contrast box" (CB), a new concept under development at Texas Instruments;and the Ford-Aerospace double-gated contrast filter.4 As part of Texas Instruments development activity, CB algorithm performance was compared with the others. To do this meaningfully, all four concepts were tested using a common data base. The measure of detection performance was the total number of candidate targets handed off to the feature extractor and classifier to achieve a specified probability of including the actual target in the total. An ideal detection algorithm in terms of this measure would only need to hand off one target (assuming only one target in the FOV) to achieve a probability of 1. Other performance measures were input and output signal-to-noise ratios (SNR) and algorithm gain. The data base used in this investigation consisted of 256 independent IR images containing targets nominally varying between 5 and 500 pixels in size. The results presented not only illustrate how the algorithm performance depends on range to the target, but show that no one algorithm is best for all values of pixels on target. Of the four, however, the contrast box appears to provide the best overall performance. © 1982 SPIE. All rights reserved.

关键词： Pixels

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Intensity correlation techniques for passive optical device detection

Intensity correlation techniques for passive optical device ...

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infrared technology for target detection and classification 1981

作者： Gustafson, Steven C. University of Dayton Research Institute 300 College Park Avenue DaytonOH45469 United States

The use of intensity correlation techniques for the detection of passive optical devices is considered. It is assumed that the devices have small angular sizes due to their large distances from the detection system, and it is assumed that the final optical apertures of the devices appear to be stationary, whereas their surroundings appear to fluctuate. This difference in apparent motion forms the basis for intensity correlation detection, which has potential advantages because of its insensitivity to phase variations due, for example, to motion of the detection system or to atmospheric turbulence. Some relationships between intensity correlation detection and certain areas in optical physics, including laser radar (lidar), intensity correlation interferometry, and speckle phenomena due to moving diffuse objects are discussed. A simple model of intensity correlation detection is developed and related to the influence of stationary coherent background illumination on the autocorrelation function in time of a coherently illuminated moving rough surface. An expression for this autocorrelation function is derived and discussed for certain elementary conditions. © 1982 SPIE. All rights reserved.

关键词： Optical radar

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infrared target array development

Infrared target array development

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infrared technology for target detection and classification 1981

作者： McIntire, Thomas O. Scott, Edward A. Methodology and Instrumentation Division U.S. Army Yuma Proving Ground STEYP-MMI YumaAZ85364 United States

A "life size" thermal target array has been developed to facilitate in-flight testing of airborne weapon systems containing night vision subsystems. This in-flight testing to measure the performance of the night vision subsystem and its effect on overall weapon system performance is essential to the test and evaluation process of the particular weapon under test. This measurement of subsystem performance is called the Modulation Transfer Function, or MTF. In addition, a laser designator subsystem is frequently incorporated in a precision guided munition weapon system. In the test and evaluation of the designator, such quantities as beam quality (energy distribution), beam divergence, and beam wander are of interest. The thermal targets may be used to evaluate armored weapon systems. The capability of providing carefully controlled and variable thermal signatures in a field test environment is considered unique. The thermal target array consists of three targets: A six bar recognition target, a two bar detection target, and a laser designator scoring board (cross-hair). The image dimensions of 2.3 meters by 2.3 meters were derived from an optimized threat envelope. The thermal signatures of the targets are controllable to within 0.3 C about a differential setpoint. This differential setpoint is measured between the active element and the target background (or "ambient"). Several differential temperature settings are available to the test officer: 1.25°C, 3°C, 5°C, 7.5°C, and 10°C. This paper reviews the thermal array test objectives, target array fabrication, methodology of target utilization, and representative results. © 1982 SPIE. All rights reserved.

关键词： Vision

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detection efficiency for large-aperture coherent laser radars

Detection efficiency for large-aperture coherent laser radar...

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Physics and technology of Coherent infrared Radar I 1981

作者： Carl Leader, J. McDonnell Douglas Research Laboratories St. LouisMO63166 United States

The heterodyne detection efficiency of a large-aperture, coherent laser radar, defined as the actual signal-to-noise ratio (SNR) divided by the ideal SNR, is derived for detected phase-front distortions resulting from atmospheric turbulence or diffuse target scattering. Specific expressions are developed for a general target reflectivity distribution and a receiver having a finite-detection aperture, local-oscillator aperture, and local-oscillator beam. Numerical calculations of the heterodyne efficiency (using the derived expressions) show the reduction in heterodyne detection-efficiency resulting from atmospheric turbulence, near-field effects, and target speckle. © 1982 SPIE. All rights reserved.

关键词： Heterodyne detection

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