Fuzzy-logic-based sensor fusion for mine and concealed weapon detection

Meitzler, Thomas; Bryk, Darryl; Sohn, Euijung; Lane, Kimberly; Raj, Jyoti; Singh, Harpreet

doi:10.1117/12.486955

Cited by 9 publications

(7 citation statements)

References 4 publications

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“…Meitzler et al 10 presented a fuzzy-logic based sensor fusion of images to combine data sets containing infrared and visual images under different types of atmospheric contrast conditions. A holographic matched-filter method is used to scan images for automated detection.…”

Section: Introductionmentioning

confidence: 99%

“…Over the years, many special editions of scientific journals, hundreds of conferences, and thousands of papers have had been tackling the problems of sensor integration based on three main facets: variety of architecture, variety of algorithms, and variety of applications [1][2][3][4][5][6][7][8][9][10][11] . Hundreds of publications solve the sensor fusion problem using Fuzzy Set theory.…”

Section: Introductionmentioning

confidence: 99%

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Intelligent control system using Dempster-Shafer theory of evidence

Hassan

2004

SPIE Proceedings

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This paper presents an intelligent control system for robust and adaptive control of non-linear, timevariant systems operating under uncertain conditions. The approach is based on Dempster-Shafer theory of evidence and Dempster's rule for combining beliefs. The approach can handle systems with multiple sensors and multiple sources of disturbance. Sensor with different and nonlinear characteristics can also be integrated in this approach.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Intelligent control system using Dempster-Shafer theory of evidence

Hassan

2004

SPIE Proceedings

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“…And image fusion algorithms based on fuzzy logic have been studied during the last two decades. These algorithms consist of utilization of fuzzy rules to fuse two images in terms of gray level values [2][3][4][5][6][7][8] and the mergence of wavelet coefficients from these two images according to the extracted features [9][10][11][12][13]. And some neural networks have also been used to generate a fuzzy inference system structure automatically from the input image data obtained from different sensors [6,7,14,15,16].…”

Section: Introductionmentioning

confidence: 99%

Multisensor image fusion using fuzzy logic for surveillance systems

Zheng

2010

2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery

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Multisensor image fusion has its effective utilization for surveillance. In this paper, we utilize a fuzzy logic approach to fuse images from different sensors, in order to enhance visualization for surveillance. With the help of fuzzy if-then rules and membership functions designed for the image data set, the fuzzy logic approach can model and combine the images to enhance the contrast of the fused image. Mamdani-type fuzzy inference system is used to combine the images. Subjective and objective image fusion performance measures are introduced to assess the performance of image fusion schemes. Experimental results show that the fuzzy logic approach is effective to fuse images from different sensors.

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“…Although the use of multiple views of the same scene has long been considered an advantage in computer vision, it is only recently that it is being considered for remote sensing approaches [1]. To date, most image fusion techniques for radar imaging are mainly applied to fuse images from different modalities, such as between optical and infra-red images [2,3,4,5]. As a result, there have been very limited studies regarding the fusion of the same scenes, obtained from the same sensor, which is crucial to multi-view through-the-wall radar imaging (TWRI).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic-Based Image Fusion for Multi-view Through-the-Wall Radar

Seng

Bouzerdoum

Tivive

et al. 2010

2010 International Conference on Digital Image Computing: Techniques and Applications

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Fuzzy logic-based image fusion for multi-view through-the-wall radar AbstractIn this paper, we propose a new technique for image fusion in multi-view through-the-wall radar imaging system. As most existing image fusion methods for through-the-wall radar imaging only consider a global fusion operator, it is desirable to consider the differences between each pixel using a local operator. Here, we present a fuzzy logic-based method for pixel-wise image fusion. The performance of the proposed method is evaluated on both simulated and real data from through-the-wall radar imaging system. Experimental results show that the proposed method yields improved performance, compared to existing methods.

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Fuzzy-logic-based sensor fusion for mine and concealed weapon detection

Cited by 9 publications

References 4 publications

Intelligent control system using Dempster-Shafer theory of evidence

Intelligent control system using Dempster-Shafer theory of evidence

Multisensor image fusion using fuzzy logic for surveillance systems

Fuzzy Logic-Based Image Fusion for Multi-view Through-the-Wall Radar

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