Cameva, A Methodology for Estimation of Target Detectability

Abstract

This paper will present a methodology for computerised evaluation of camouflage effectiveness. The methodology is implemented in software at Danish Defence Research Establishment (DDRE) under the acronym CAMEVA. Basic input is a single image comprising a highly resolved static target as well as a proper amount of representative background. Separate target and background images can also be handled. Target and background regions are manually selected using the computer's standard pointing device (i.e. the mouse). From the input data, CAMEVA predicts the target detectability as a function of the target distance. The detectability estimate is based on statistical distributions of features extracted from the imagery, establishing a multidimensional feature space. In the feature space, the Bhattacharyaa distance measure is applied as an estimator of the separability' between the target and the background. The intention is that the extracted features should resemble those applied during the human perception process. Typically, contrast and various measures of edge strength are applied. The Bhattacharyaa distance establishes a relative separability, while the absolute detection range is obtained by deriving a relation between the Bhattacharyaa distance and the estimated target resolution, at range. Thus by introducing parameters of the sensor, typically the human unaided eye, detectability as a function of the range is obtained. The methodology will not reflect individual observer performance but is aimed at providing an estimate of the optimal detection performance, given the selected set of features. During the choice of features and of sensor parameters, other perception mechanisms, than the human observer performance, can be modelled with this methodology. The paper will discuss theoretical and practical aspects of CAMEVA.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2000
Accession Number
ADP010535

Entities

People

  • Christian M. Birkemark

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Computational Science
  • Contrast
  • Data Analysis
  • Decision Theory
  • Detection
  • Detectors
  • Digital Image Processing
  • Digital Images
  • Feature Extraction
  • Image Processing
  • Information Processing
  • Observation
  • Observers
  • Probability
  • Statistical Distributions
  • Target Acquisition

Readers

  • Computational Modeling and Simulation
  • Sensor Fusion and Tracking Systems.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space
  • Space - Space Objects