An image segmentation method based on Mumford–Shah model with mask factor and neighborhood factor

Pattern Analysis and Applications - A novel image segmentation model is proposed to improve the stability of existing segmentation methods. In the proposed model, we introduce two factors into the...     

Möbius-invariant curve and surface energies and their applications

The sphere is a natural and seamless parametric domain for closed genus-0 surfaces. We introduce an efficient hierarchical optimization approach for the computation of spherical parametrization for closed genus-0 surfaces by minimizing a nonlinear energy balancing angle and area distortions. The mapping results are bijective and lowly distorted. Our algorithm converges efficiently and is suitable to manipulate large-scale geometric models. We demonstrate and analyze the effectiveness of our mapping in spherical harmonics decomposition.     

Mbius-invariant curve and surface energies and their applications

Curvature-based surface energies are frequently used in mathematics, physics, thin plate and shell engineering, and membrane chemistry and biology studies. Invariance under rotations and shifts makes curvature-based energies very attractive for modeling various phenomena. In computer-aided geometric design, the Willmore surfaces and the so-called minimum variation surfaces （MVS） are widely used for shape modeling purposes. The Willmore surfaces are invariant w.r.t conformal transformations （Mbius or conformal invariance）, and studied thoroughly in differential geometry and related disciplines. In contrast, the minimum variation surfaces are not conformal invariant. In this paper, we suggest a simple modification of the minimum variation energy and demonstrate that the resulting modified MVS enjoy Mbius invariance （so we call them conformal-invariant MVS or, shortly, CI-MVS）. We also study connections of CI-MVS with the cyclides of Dupin. In addition, we consider several other conformal-invariant curve and surface energies involving curvatures and curvature derivatives. In particular, we show how filtering with a conformal-invariant curve energy can be used for detecting salient subsets of the principal curvature extremum curves used by Hosaka and co-workers for shape quality inspection purposes.     

Image segmentation scheme based on SOM–PCNN in frequency domain

A hybrid scheme for the image segmentation of high-resolution images is proposed in this study. Our methodology is based on combining both supervised and unsupervised segmentation. The entire process is performed in the frequency domain, rather than the spatial domain, using the Shift Invariant Shearlet Transform (SIST). Initially, the input image is filtered using an anisotropic filter to enhance the texture features. Then, it is separated into low and high sub-band frequencies using SIST. Subsequently, we built a feature vector from coarser coefficients complemented with texture information extracted from high-frequency coefficients of the input image. SOM is used for the preliminary classification of the input image coefficients, and the network training process is performed using the previously built feature vector. Lastly, the modified PCNN is used to augment the SOM results to reduce the over-segmentation artefacts. We used the Berkeley Segmentation Database (BSR) and Quick-Bird Satellite images to validate the results. It was found that the proposed scheme is superior to the Fuzzy-C-Means-based, SOM-based, and PCNN-based segmentation algorithms in terms of quantitative criteria and visual interpretation.     

A blind video watermarking scheme based on ICA and shot segmentation

With the development of network and multimedia techniques, the digital video copyright protection issues have become more and more important as digital video can be easily pro- duced, replicated, accessed and distributed. Digital video watermark is the ma…     

Special issue on “Soft computing techniques: applications and challenges” neural computing and applications

Neural Computing and Applications -     

Commentary on “A new generalized improved score function of interval-valued intuitionistic fuzzy sets and applications in expert systems”

In this paper, we demonstrate that the Theorem 3.1 in a recently published paper by Garg [Appl. Soft Comput. 38 (2016) 988–999] is incorrect by a counterexample. Further, we point out the shortcomings of Garg's proposed generalized improved score function for practical decision making.     

Multi-feature sea–land segmentation based on pixel-wise learning for optical remote-sensing imagery

Robust sea–land segmentation in optical remote-sensing images is challenging because of the complex sea–land environment and scene diversity. Here, we propose a novel multi-feature sea–land segmentation method via pixel-wise learning for optical remote-sensing images. Multiple features such as greyscale, local statistical information, edge, texture, and structure are first extracted from each pixel in training images and then used to learn a multi-feature sea–land classifier, which transforms the segmentation issue into pixel-wise binary classification problem. In our approach, a new multi-feature sea–land segmentation algorithm is put forward based on the approximation of Newton method. Experiments on Google-Earth, Venezuelan Remote Sensing Satellite-1 (VRSS-1) and Gaofen-1 images demonstrate that the proposed approach yields more robust and accurate sea–land segmentation results.     

Influences of data filtering on human–computer interaction by gaze-contingent display and eye-tracking applications

We describe an interactive gaze-contingent display (GCD) applied to clinical applications; the system uses a simple texture hole to inhibit peripheral vision, to test and stress overt mechanisms of visual searching in normal subjects. The correct use of GCD in vision research is affected by tremor of the hole, due to system noise, nystagmus, eye blinking, calibration and subject reactivity. These issues compromise the execution of task. In order to obtain a stable GCD hole, we implemented a predictive gaze-contingent display (PGCD), fitting through dispersion of fixations and modulating a filter. The paper describes the PGCD and compare it with the common technique, providing evidence that humans fit exploration based on the characteristics of the computer system; in particular we found significant difference applying PGCD or a simple finite impulse response filter. We suggest that a correct human–computer interaction applied to neuropsychological context must be developed taking in consideration both technical point of view and human behavior.     

A multilevel image thresholding segmentation algorithm based on two-dimensional K–L divergence and modified particle swarm optimization

Multilevel image segmentation is a technique that divides images into multiple homogeneous regions. In order to improve the effectiveness and efficiency of multilevel image thresholding segmentation, we propose a segmentation algorithm based on two-dimensional (2D) Kullback–Leibler(K–L) divergence and modified Particle Swarm Optimization (MPSO). This approach calculates the 2D K–L divergence between an image and its segmented result by adopting 2D histogram as the distribution function, then employs the sum of divergences of different regions as the fitness function of MPSO to seek the optimal thresholds. The proposed 2D K–L divergence improves the accuracy of image segmentation; the MPSO overcomes the drawback of premature convergence of PSO by improving the location update formulation and the global best position of particles, and reduces drastically the time complexity of multilevel thresholding segmentation. Experiments were conducted extensively on the Berkeley Segmentation Dataset and Benchmark (BSDS300), and four performance indices of image segmentation – BDE, PRI, GCE and VOI – were tested. The results show the robustness and effectiveness of the proposed algorithm.     

Efficient software–hardware 3D heat equation solver with applications on the non-destructive evaluation of minefields

This paper targets the efficient computational solution of the heat transfer processes that take place in the soil and at the soil–air interface and its use in non-destructive evaluation (NDE) techniques. In particular, the problem of the detection of plastic antipersonnel mines is considered. To this aim we projected a 3D finite-difference (FD) thermal model of the soil on a FPGA platform using Handel-C and VHDL. A speedup factor of 34 over a purely software solution is achieved, obtaining processing times that permit the use of the system on the field.     

Collaborative applications over peer-to-peer systems–challenges and solutions

Emerging collaborative Peer-to-Peer (P2P) systems require discovery and utilization of diverse, multi-attribute, distributed, and dynamic groups of resources to achieve greater tasks beyond conventional file and processor cycle sharing. Collaborations involving application specific resources and dynamic quality of service goals are stressing current P2P architectures. Salient features and desirable characteristics of collaborative P2P systems are highlighted. Resource advertising, selecting, matching, and binding, the critical phases in these systems, and their associated challenges are reviewed using examples from distributed collaborative adaptive sensing systems, cloud computing, and mobile social networks. State-of-the-art resource discovery/aggregation solutions are compared with respect to their architecture, lookup overhead, load balancing, etc., to determine their ability to meet the goals and challenges of each critical phase. Incentives, trust, privacy, and security issues are also discussed, as they will ultimately determine the success of a collaborative P2P system. Open issues and research opportunities that are essential to achieve the true potential of collaborative P2P systems are discussed.     

Numerical analysis on electroosmotic flows in a microchannel with rectangle-waved surface roughness using the Poisson–Nernst–Planck model

The present study has numerically investigated two-dimensional electroosmotic flows in a microchannel with dielectric walls of rectangle-waved surface roughness to understand the roughness effect. For the study, numerical simulations are performed by employing the Nernst–Planck equation for the ionic species and the Poisson equation for the electric potential, together with the traditional Navier–Stokes equation. Results show that the steady electroosmotic flow and ionic-species transport in a microscale channel are well predicted by the Poisson–Nernst–Planck model and depend significantly on the shape of surface roughness such as the amplitude and periodic length of wall wave. It is found that the fluid flows along the surface of waved wall without involving any flow separation because of the very strong normal component of EDL (electric double layer) electric field. The flow rate decreases exponentially with the amplitude of wall wave, whereas it increases linearly with the periodic length. It is mainly due to the fact that the external electric-potential distribution plays a crucial role in driving the electroosmotic flow through a microscale channel with surface roughness. Finally, the present results using the Poisson–Nernst–Planck model are compared with those using the traditional Poisson–Boltzmann model which may be valid in these scales.     

Effect of fractional parameter on plane waves of generalized magneto–thermoelastic diffusion with reference temperature-dependent elastic medium

The present paper is concerned with the investigation of disturbances in a homogeneous, isotropic reference temperature-dependent elastic medium with fractional order generalized thermoelastic diffusion. The formulation is applied to the generalized thermoelasticity based on the fractional time derivatives under the effect of diffusion. The analytical expressions for displacement components, stresses, temperature field, concentration and chemical potential are obtained in the physical domain by using the normal mode analysis technique. These expressions are calculated numerically for a copper-like material and depicted graphically. Effect of fractional parameter and presence of diffusion is analyzed theoretically and numerically. Comparisons are made with the results predicted by the fractional and without fractional order in the presence and absence of diffusion.