A multi-object image segmentation C–V model based on region division and gradient guide

The Chan–Vese (C–V) model is an ineffective method for processing images in which the intensity is inhomogeneous. This is especially true for multi-object segmentation, in which the target may be missed or excessively segmented. In addition, for images with rich texture information, the processing speed of the C–V is slow. To overcome these problems, this paper proposes an effective multi-object C–V segmentation model based on region division and gradient guide. First, a rapid initial contour search is conducted using Otsu’s method. This contour line becomes the initial contour for our multi-object segmentation C–V model based on a gradient guide. To achieve the multi-object segmentation the image is then converted to a single level set whose evolution is controlled using an adaptive gradient. The feasibility of the proposed model is analyzed theoretically, and a number of simulation experiments are conducted to validate its effectiveness.     

Reordering for improving global Arnoldi–Tikhonov method in image restoration problems

This paper discusses the solution of large-scale linear discrete ill-posed problems arising from image restoration problems. Since the scale of the problem is usually very large, the computations with the blurring matrix can be very expensive. In this regard, we consider problems in which the coefficient matrix is the sum of Kronecker products of matrices to benefit the computation. Here, we present an alternative approach based on reordering of the image approximations obtained with the global Arnoldi–Tikhonov method. The ordering of the intensities is such that it makes the image approximation monotonic and thus minimizes the finite differences norm. We present theoretical properties of the method and numerical experiments on image restoration.     

A restoration–segmentation algorithm based on flexible Arnoldi–Tikhonov method and Curvelet denoising

In this paper, we illustrate a two-stage algorithm consisting of restoration and segmentation to reach binary segmentation from the noisy and blurry image. The results of our method can be applied in main fields of the image processing such as object extraction. In the first stage, we have a linear discrete ill-posed problem with a noise-contaminated right-hand side, arising from the image restoration. We consider problems in which the coefficient matrix is the sum of Kronecker products of matrices and present a global flexible Arnoldi–Tikhonov method coupled with the generalized cross-validation for the computation of the regularization parameter at each iteration. The proposed algorithm is based on the global Arnoldi method that allows using a more flexible solution subspace. In the second stage, we segment the restored image in order to reach a binary image in which the target object is emphasized. In our segmentation method, we use Gaussian scale-space technique to compute discrete gradients of the restored image for pre-segmenting. Also, in order to denoise, we use a tight frame of Curvelet transforms and thresholding which is based on the principle obtained by minimizing Stein’s unbiased risk estimate. This algorithm has an iterative part based on the iterative part of TFA (Cai et al. in SIAM J Imaging 6(1):464–486, 2013), but we use eigenvectors of Hessian matrix of image for improving this part. Theoretical properties of the method of both stages and numerical experiments are presented.     

Visual saliency’s modulatory effect on just noticeable distortion profile and its application in image watermarking

Perceptual watermarking should take full advantage of the results from human visual system (HVS) studies. Just noticeable distortion (JND) gives us a way to model the HVS accurately. In this paper, another very important aspect affecting human perception, visual saliency, is introduced to modulate JND model. Based on the visual saliency’s modulatory effect on JND model which incorporates visual attention’s influence on visual sensitivity, the saliency modulated JND profile guided image watermarking scheme is proposed. The saliency modulated JND profile guided watermarking scheme, where the visual sensitivity model combined with visual saliency’s modulatory effect is fully used to determine image-dependent upper bounds on watermark insertion, allows us to provide the maximum strength transparent watermark. Experimental results confirm the improved performance of our saliency modulated JND profile guided watermarking scheme in terms of transparency and robustness. Our watermarking scheme is capable of shaping lower injected-watermark energy onto more sensitive regions and higher energy onto the less perceptually significant regions in the image, which yields better visual quality of the watermarked image. At the same time, the proposed saliency modulated JND profile guided image watermarking scheme is more robust compared to unmodulated JND profile guided image watermarking scheme.     

Tracking moving object using Snake’s jump based on image flow

An active contour model, Snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid (i.e. deformable) objects by Kass in 1987. Snake is designed on the basis of Snake energies. Segmenting and tracking can be executed successfully by the process of energy minimization. The ability to contract is an important process for segmenting objects from images, but the contraction forces of Kass’ Snake are dependent on the object’s form. In this research, new contraction energy, independent of the object’s form, is proposed for the better segmentation of objects. Kass’ Snake can be applied to the case of small changes between images because its solutions can be achieved on the basis of variational approach. If a somewhat fast moving object exists in successive images, Kass’ Snake will not operate well because the moving object may have large differences in its position or form, between successive images. Snake’s nodes may fall into the local minima in their motion to the new positions of the target object in next image. When the motion is too large to apply image flow energy to tracking, a jump mode is proposed for solving the problem. The vector used to make Snake’s nodes jump to the new location can be obtained by processing the image flow. The effectiveness of the proposed Snake is confirmed by some simulations.     

A new method for the fast determination of the data retention lifetime of UV EPROM’s

The newly developped method involves a controlled partial erasure of a charged ultraviolet erasable programmable read only memory device followed by a period of high temperature storage. The model is based on two assumptions: the amount of charge stored at the floating gate of a programmed cell is assumed to be equal throughout a component and the trip the minimum level of charge stored at the floating gate of a programmed cell, has a Gaussian distribution throughout a component. The experimental data are well described by the model. After implementation of the experimental results in the model we extrapolate the data retention lifetimes of the UVEPROM’S under operational conditions. Our measurements show that most of the tested UVEPROM devices (64 ko to 256 ko) have a similar operational lifetime, only the charge leakage activation energy differs (0.35 to 0.9 eV) depending on the type of component. In conclusion this method and model are suitable for a fast determination of UVEPROM’S data retention lifetimes under operational conditions.     

Design method of Chua’s circuit for specified spectrum distribution

Based on the α-β bifurcation curves and the special characteristics of chaotic spectrum of chua’s circuit, this paper presents here a method for designing a Chua’s circuit which approximately satisfy specified spectrum distribution range. Supported by the Nature Science Foundation of Zhejiang Province     

Social networks’ unnoticed influence on body image in Spanish university students

The influence of advertising on social networks and its effect on young people’s self-image has been studied. This study first explored the frequency of published videos reposted on social networks using different Application Programming Interfaces as search engines. The study also implemented self-valuation surveys assessed by experts and distributed among mental health professionals who assessed the influence of these social networks. Finally, the survey was designed regarding social networks and body assessment and distributed among Córdoba university students (N = 328). The majority of health professionals concluded that there is an elevated influence of social networks on eating disorders, assessing advertising as a risk factor with a value of 4.60 out of 5. Young people’s perceptions of their body image indicate that women’s degree of satisfaction is highly correlated with the frequency of their connections to social networks, with the body image those women present and with the effect of advertising. Conversely, this high correlation and influence does not exist in men.     

I2C 总线 A/D、D/A 转换器

使用串行I^2C总线，使单片机硬件系统的设计具有简单、紧凑、易于维护、故障率低的特点。介绍了新型A/D、D/A转换器芯片的软硬件设计方法。     

A multiphase level set formulation for image segmentation using a MRF-based nonsymmetric Student’s-<Emphasis Type="Italic">t</Emphasis> mixture model

This paper proposes a new level set energy function framework in which the Markov random field-based nonsymmetric Student’s-t mixture model (SMM) is incorporated for labelling static images. This framework provides a general strategy by taking the best components of the Bayesian theory and level set technique. Therefore, the proposed segmentation method can bring the topology shape constraints to a statistical finite mixture model. An advantage of this method is that it can overcome the weakness of the conventional level set formulation by filtering out the outliers and stopping at the boundary points. Another feature is that the local relationship among neighbouring pixels is introduced into the prior probability so that the proposed framework is more robust against noise. The method is mainly implemented by modelling the probability density function of the observed data using nonsymmetric SMM. The proposed model has a simplified structure, which effectively reduces the computational complexity. Finally, numerical experiments on various synthetic, real-world images are conducted.     

A Model for Identifying the Behavior of Alzheimer’s Disease Patients in Smart Homes

Wireless Personal Communications - In recent years, Smart Cities and Smart Homes have been studied as an important field of research. The design and construction of smart homes have flourished so...     

Social media and political partisanship – A subaltern public sphere’s role in democracy

Social media, as a subaltern public sphere (Fraser, 1990), have a democratic function in providing an alternative platform for minorities and marginalized to defy mainstream discourses in the public sphere. However, social media have been found to have an echo chamber effect, which may be detrimental to democracy. They may help to accelerate the ascendancy of a “post-truth” era in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief. A study on political polarization, however, showed that selective exposure and avoidance in social media are weak indicators of polarization (Johnson et al., 2017). This study examines the role of social media in democracy and partisan politics. The authors considered that despite the echo chamber effect, social media have a limited part to play in the formation of polarized stances compared with other factors, such as demographics, political orientation, and mass media use. The study tested two main hypotheses: H1: Social media use is associated with political stance that is marginalized in the mainstream media; H2: Political orientation has a stronger relationship than social media use with the stance toward political values and social issues.The results supported both hypotheses. Social media are associated with political stance that is marginalized in the mainstream media. However, when compared with other factors, the relationship between social media and stance becomes less obvious. Although the echo chamber effect may reinforce the original stance, social media do not exhibit a strong relationship with the stance toward political values and social issues. Partisan orientation and use of partisan mass media are found to have stronger links with variations in stance. Social media, however, provide a subaltern public sphere for those excluded from the dominant public sphere, thus extending the public sphere to accommodate multiple opinions and perspectives.     

A new authentication based cheating prevention scheme in Naor–Shamir’s visual cryptography

Visual cryptography (VC), first presented by Naor and Shamir, is a variant of secret sharing, thus it also called visual secret sharing. It can be widely used in many applications such as encrypting large data efficiently. In the literature, the problem of cheating is under consideration in secret sharing. Recently, Horng et al. pointed out that cheating is possible in k-out-of-n VC schemes, and presented two kinds of the cheating prevention schemes for protecting honest participants. One of them is the authentication based cheating prevention scheme. In this paper, we analyze the definition of cheating prevention and propose a new authentication based cheating prevention scheme. This scheme is constructed with Naor–Shamir’s VC scheme. Finally, we give the security analysis to prove that the proposed scheme is immune to cheating.     

Quadtree-based non-local Kuan’s filtering in video compression

Transform coding has been widely used in video coding standards, such as H.264 advanced video coding (H.264/AVC) and high efficiency video coding (HEVC). But the coded video sequences suffer from annoying coding artifacts, such as blocking and ringing artifacts. In this paper, we propose the quadtree-based non-local Kuan’s (QNLK) filter to suppress the quantization noise optimally and improve the objective and subjective quality of the reconstructed frame simultaneously. The proposed filter takes advantage of the non-local Kuan’s (NLK) filter to restore the quantized signal in transform domain. Restored coefficients are then projected onto designed quantization constraint sets (QCS). Quadtree-based signaling strategy is used at the end of QNLK for adaptive filtering on/off control. Experimental results of QNLK show that the proposed method achieves significant objective coding gain and visual quality improvement, compared with both H.264/AVC high profile and HEVC.     

Improved method for searching interleavers from a certain set using Garello’s method with applications for the LTE standard

In this paper, we propose a method for searching interleavers within a certain class, with the aim of designing turbo codes with good distance spectrum. The method is based on a modified version of Garello’s algorithm and consists in the calculation of frame error rate truncated upper bound. Here, it is applied to quadratic permutation polynomial (QPP) interleavers able to outperform those chosen for the long-term evolution (LTE) standard, for lengths up to 1,504 bits. Three classes of interleavers have been analyzed: (1) the set of QPP interleavers with the largest spread, (2) the set of QPP interleavers with a spread parameter equal to that of LTE interleaver and the highest refined nonlinearity degree, and (3) the complete set of all QPP interleavers for lengths up to 1,008. The distance spectrum optimization is made for all classes. Compared to previous methods for finding QPP-based interleavers, the search complexity is reduced, with improved performances in terms of search time, allowing interleavers of higher length. For lengths up to approximately 450, the best interleavers were found in the first class. For longer lengths, the second class contained the best ones.     

Enhancing Prony’s method by nuclear norm penalization and extension to missing data

Prony’s method is a widely used method for modelling signals using a finite sum of exponential terms. It has innumerable applications in weather modelling, finance, medical signal analysis, image compression, time series analysis, power grids, etc. Prony’s method has, however, the reputation of being unstable with respect to noise perturbations. The goal of the present paper is to assess the potential improvements of a nuclear-norm-penalized regularization of Prony’s method. The nuclear norm regularization is a standard technique for improving the performance when processing noisy signals with low-rank underlying structure such as in matrix completion, matrix compressed sensing, hidden variable models. We consider both the standard setting and the case of missing data. We provide a fast estimation algorithm for the nuclear-norm-penalized least-squares minimization. Monte Carlo experiments show that regularization can significantly enhance the performance of Prony’s method with and without missing data.     

Mixed-Mode Oscillations in a Modified Chua’s Circuit

We consider a singularly perturbed system of differential equations of the form ε u′=g(u,v,λ), v′=f(u,v,λ), where (u,v)∈R ³, 0<ε?1, and λ is a set of parameters. Such a system describes a modified Chua’s circuit with mixed-mode oscillations (MMOs). MMOs consist of a series of small-amplitude oscillations (canard solutions) and large-amplitude relaxations. In the paper we provide a series of both numerical and analytical analyses of the singularly perturbed system for the modified Chua’s circuit with nonlinear f and g. In particular, we analyze the occurrence of the Farey sequence $\it L^{s}$ , where $\it L$ and $\it s$ are the numbers of large and small oscillations, respectively.