Many steganographic algorithms have been proposed until these days. They all try to hide information by relying on some of well-known techniques. However, each of these techniques has its advantages and also its drawb...
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Many steganographic algorithms have been proposed until these days. They all try to hide information by relying on some of well-known techniques. However, each of these techniques has its advantages and also its drawbacks. In this paper, we have investigated a possibility of using tool known as Mojette Transform for modifying and scrambling a binary image containing secret information. The image after these processes should resemble noisy picture. Modified image is then embedded into the least significant bit plane of cover image. The used techniques should result in better values of parameters as MSE, or PSNR in comparison with performance of the classical Least Significant Bit steganography.
This paper demonstrates the adaptive illumination methods for the implementations of Colorimetric (also known as absorbance detection), Fluorescence and Luminescence ELISA models using a standalone or mobile imaging s...
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ISBN:
(纸本)9781467387224
This paper demonstrates the adaptive illumination methods for the implementations of Colorimetric (also known as absorbance detection), Fluorescence and Luminescence ELISA models using a standalone or mobile imaging setup with data processing techniques and prediction algorithms. These ELISA modelling systems, mainly depend on the quality of the images and the imageprocessingalgorithms employed for accuracy and reliability. The assay concentration estimations for such systems are greatly dependent upon the light absorbance and transmittance properties of the chemical compounds that make up the analytic biochemistry assay and are highly influenced by the quality and intensity of the backlight panel used in these device setups. The goal is to develop an independent lighting module which would subsequently result in better images, and a more accurate system that would be applicable for a wide variety of ELISA imaging systems.
The algorithm of spatio-temporal ultrawideband (UWB) signal processing for radiometric imaging is synthesized and investigated. Analytical expressions for the limiting error of the radiometric image estimate and ambig...
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ISBN:
(纸本)9781509010516
The algorithm of spatio-temporal ultrawideband (UWB) signal processing for radiometric imaging is synthesized and investigated. Analytical expressions for the limiting error of the radiometric image estimate and ambiguity function of system are derived. The possibility of ambiguity function formation with one main lobe in the UWB cross-correlation and compensation system with ultra-sparse antenna array is substantiated. The simulation examples of radiometric imaging are shown.
Pedestrian segmentation in infrared images is a difficult problem for the defects of low SNR and inhomogeneous luminance distribution. In this paper, we propose a method which aims to obtain the accurate pedestrian se...
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ISBN:
(纸本)9781467399623
Pedestrian segmentation in infrared images is a difficult problem for the defects of low SNR and inhomogeneous luminance distribution. In this paper, we propose a method which aims to obtain the accurate pedestrian segmentation through a background prior and boundary weight-based saliency. Background likelihood is firstly calculated as background prior to get an abstract representation for infrared pedestrian. Then, by considering the object-center prior, the object-biased Gaussian model is applied to derive the probability density estimation for pedestrians. Finally, the above two results are integrated with the boundary weight to obtain the final saliency map for infrared image, based on which pedestrians can be easily segmented. Experimental results on real infrared images captured by intelligent transportation systems demonstrate the effectiveness of the proposed approach against the state-of-the-art algorithms.
In this paper, distributed optimization problem is investigated under a second-order multi-agent network, in which each agent is described as the double integrator. The multi-agent network is introduced for solving a ...
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ISBN:
(纸本)9781509009107
In this paper, distributed optimization problem is investigated under a second-order multi-agent network, in which each agent is described as the double integrator. The multi-agent network is introduced for solving a large scale optimization problem by the cooperation of coupled agents. Based on the interaction over the network, the optimal solution of the problem can be obtained. Since the existing distributed algorithms for second-order multi-agent network enforce each agent to transmit complete information(both state information and derivation information of the independent variable, i.e., corresponded position and velocity information of the agent), this paper is motivated to design the distributed algorithm with only using the position information of neighbors, which reduces the requirement on communication bandwidth. With the help of Lyapunov analysis and La Sallel's Invariance Principle, the optimal solution is derived and the optimization problem is solved via the second-order multi-agent network. Finally, a numerical example is presented to illustrate the theoretical result.
Mammogram images are now increasingly acquired with full-field digital mammography (FFDM) systems in the clinics. Traditionally, the "for-processing" format of FFDM images is used in computer-aided diagnosis...
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ISBN:
(纸本)9781467399623
Mammogram images are now increasingly acquired with full-field digital mammography (FFDM) systems in the clinics. Traditionally, the "for-processing" format of FFDM images is used in computer-aided diagnosis (CAD) of breast cancer. In this study, we investigate the feasibility of using "for-presentation" format of FFDM (which are more readily available) in development of CAD algorithms for microcalcification (MC) lesions. We conduct a quantitative evaluation of both the image features and the detectability of individual MCs on a set of 188 mammograms acquired in both formats. The results demonstrate that there is a high degree of agreement in the image features between the two image formats, and that a slight increase in false-positives in MC detection is observed in for-presentation images.
This paper presents a novel approach for the optimization of calibration parameters in structured light system (SLS). Different with conventional calibration algorithms, the proposed optimization algorithm is implemen...
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ISBN:
(纸本)9781467399623
This paper presents a novel approach for the optimization of calibration parameters in structured light system (SLS). Different with conventional calibration algorithms, the proposed optimization algorithm is implemented in 3D space instead of 2D image space. The object used for parameter optimization can be a simple plane with some markers. A global optimal function is constructed to contain all the intrinsic and extrinsic parameters of the SLS. Using the primary calibration parameters by conventional methods as initial values, the optimal function can be solved by minimizing the 3D measurement errors like distance, angle between markers, and the planarity of the reference plane. Experimental results show that, 3D reconstruction accuracy can be greatly improved by the proposed approach in comparison with traditional SLS calibration methods.
Feature of modern info communication systems is expeditious exchange of information that makes a problem of ensuring quality and reliability of the obtained information actual. For elimination or minimization of the d...
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ISBN:
(纸本)9781509040513
Feature of modern info communication systems is expeditious exchange of information that makes a problem of ensuring quality and reliability of the obtained information actual. For elimination or minimization of the destabilizing impact of noise and hindrances in such systemsvarious methods and algorithms of preliminary information processing are widely used, in particular, procedures of digital filtration of signals and images. Procedure of creation of the nonlinear SvD filter with adaptation to local properties of an observed signal is stated. Comparative examples of filtration of hindrances in a problem of processing of images are given, efficiency of the offered method is shown. The lines of further researches are defined.
This paper presents two algorithms for detection of plain copy-move regions—fully matching fragments—in images. Both algorithms represent data of the fragment in the form of a hash value, where the hash function is ...
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The explosion of computational imaging has seen the frontier of imageprocessing move past linear problems, like denoising and deblurring, and towards non-linear problems such as phase retrieval. There has a been a co...
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ISBN:
(纸本)9781467399623
The explosion of computational imaging has seen the frontier of imageprocessing move past linear problems, like denoising and deblurring, and towards non-linear problems such as phase retrieval. There has a been a corresponding research thrust into non-linear image recovery algorithms, but in many ways this research is stuck where linear problem research was twenty years ago: Models, if used at all, are simple designs like sparsity or smoothness. In this paper we use denoisers to impose elaborate and accurate models in order to perform inference on generalized linear systems. More specifically, we use the state-of-the-art BM3D denoiser within the Generalized Approximate Message Passing (GAMP) framework to solve compressive phase retrieval in a variety of different contexts. Our method demonstrates recovery performance equivalent to existing techniques using fewer than half as many measurements. This dramatic improvement in compressive phase retrieval performance opens the door for a whole new class of imaging systems.
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