Assessing camouflage methods using textural features

Nyberg, Sten

doi:10.1117/1.1390295

Cited by 19 publications

(10 citation statements)

References 15 publications

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“…From the local responses invariant features are calculated. The features used are described in a previous paper 11 , even if that description is based on features computed using the Fourier transform. For a more complete description of the vehicle, several features should be used.…”

Section: Theorymentioning

confidence: 99%

Methods for validation of optical signature models

Nelsson

Andersson

Boerjesson

et al. 2005

Targets and Backgrounds XI: Characterization and Representation

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When using prediction programs for optical signatures, it is necessary to include validations to find estimates of the uncertainties and define the regions of validity. In this paper we present two paths of development of validation methods: The objective of the first path is to analyze and validate the differences between simulated and measured images, through image features such as edge concentration and different energy measures. In particular, aspects that are important for detection, classification and identification of targets are considered. The second path concerns development of methods for quantifying the propagation of input data uncertainties to output parameters in computational predictions. Two commercial codes have been used for the modeling: RadThermIR for thermal predictions of the targets and CAMEO-SIM for the radiometry and rendering. A recently developed interface between the two codes has been utilized. For the validation of spatial statistics, several feature values have been computed for a measured image and for the corresponding simulated image. It was found that the agreement was quite good. The work on propagation of uncertainties in computational predictions has resulted in a number of proposed methods. In this paper we present two different methods: one based on linear error propagation and one based on the Monte Carlo method. The results are according to expectations for both types of methods and show that a large part of the uncertainty in predicted temperature emanates from input parameter uncertainties for the considered test case.

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Section: Theorymentioning

confidence: 99%

Methods for validation of optical signature models

Nelsson

Andersson

Boerjesson

et al. 2005

Targets and Backgrounds XI: Characterization and Representation

Self Cite

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“…Photo-simulation by using human observers as an assessment method of camouflage effectiveness has been used in various forms in the recent decades [1][2][3][4]. Other methodologies have also been tested out, involving video surveillance [5], simulation of human vision [6][7][8][9][10][11], similarity measures of target-background by image analysis techniques [2,11], assessment by simulation of target vehicles against different backgrounds [12], and image sequences taken by approaching sensors [13].…”

Section: Introductionmentioning

confidence: 98%

Search by photo methodology for signature properties assessment by human observers

Selj

Heinrich

2015

SPIE Proceedings

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Reliable, low-cost and simple methods for assessment of signature properties for military purposes are very important. In this paper we present such an approach that uses human observers in a search by photo assessment of signature properties of generic test targets. The method was carried out by logging a large number of detection times of targets recorded in relevant terrain backgrounds. The detection times were harvested by using human observers searching for targets in scene images shown by a high definition pc screen. All targets were identically located in each "search image", allowing relative comparisons (and not just rank by order) of targets. To avoid biased detections, each observer only searched for one target per scene. Statistical analyses were carried out for the detection times data. Analysis of variance was chosen if detection times distribution associated with all targets satisfied normality, and non-parametric tests, such as Wilcoxon's rank test, if otherwise. The new methodology allows assessment of signature properties in a reproducible, rapid and reliable setting. Such assessments are very complex as they must sort out what is of relevance in a signature test, but not loose information of value. We believe that choosing detection times as the primary variable for a comparison of signature properties, allows a careful and necessary inspection of observer data as the variable is continuous rather than discrete. Our method thus stands in opposition to approaches based on detections by subsequent, stepwise reductions in distance to target, or based on probability of detection.

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“…Gilmore [7] described the vision model and how the model was being used to compare different synthetic images to understand the factors affecting target conspicuity. Sten [8] applied texture descriptors to quantify the similarity between different parts of an image. In addition, other descriptors were used to distinguish man-made object characteristics.…”

Section: Introductionmentioning

confidence: 99%

A New Camouflage Texture Evaluation Method Based on WSSIM and Nature Image Features

Song¹,

Wang²

2010

2010 International Conference on Multimedia Technology

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Traditional evaluation method of camouflage texture effect is subjective evaluation. It's very tedious and inconvenient to direct the texture designing. In this paper, a systemic and rational method for direction and evaluation of camouflage texture designing is proposed. A new camouflage texture evaluation method based on WSSIM (Weight structural similarity) is given to access the effects of camouflage texture at first. Then nature image features between the camouflage texture and the background image are calculated to help direct the designing camouflage texture. Primary experimental results show that the proposed method is helpful for evaluation and design of the camouflage texture.

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Assessing camouflage methods using textural features

Cited by 19 publications

References 15 publications

Methods for validation of optical signature models

Methods for validation of optical signature models

Search by photo methodology for signature properties assessment by human observers

A New Camouflage Texture Evaluation Method Based on WSSIM and Nature Image Features

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