Dimensional Multi Research Articles

Low Dimensional Multi Class Steganalysis of Spatial LSB based Stego Images Using Textural Features

Image steganalysis ranges from detecting the presence of covert information in an image (passive steganalysis) to extraction of the information from the stego image (active steganalysis). One of the steps in active steganalysis is determining the stego algorithm used to produce the stego image. In this paper, a low dimensional combination of textural features is adapted for steganalysis. Also a novel blind statistical steganalyser to determine the spatial domain Least Significant Bit (LSB) based algorithms using one against one multi class classification is proposed. The proposed steganalyser is a multiclass ensemble Fisher Linear Discriminant (FLD) classifier that uses novel low dimensional textural features for steganalysis. The performed experiments on the Bossbase database for 5 different LSB based algorithms for 8 different payloads show that the results are much better than the state of art steganalyser.

Uncertain Multi Level Four Dimensional Multi Item Fractional Transportation Problem

Uncertain Multi Level Four Dimensional Multi Item Fractional Transportation Problem

Nonlinear Effect and MAI Impact on SAC-OCDMA System Based on 2D Multi-Diagonal Code and Laser Array

A new architecture for Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA) system based on two Dimensional Multi Diagonal (2D-MD) codes named 2D-MD SAC-OCDMA and utilizing a laser optical source is proposed for Long-Reach Passive Optical Network (LR-PON). In this work, a computer simulator tool is used, for the first time, as a SAC-OCDMA simulation set-up utilizing the unique combination of a coherent laser array and 2D-MD codes. In addition, the system performance is addressed numerically by taking into account Multiple Access Interference (MAI), optical coherent source noise, first, second and third order fiber dispersion, nonlinear effects and photo-detector noise. Simulation results indicate that for a single user (i.e., without considering MAI), the system can operate at a maximum bit rate of 55 Gb/s over 250 km of Single Mode Fiber (SMF), with a Bit Error Rate (BER) below 10−9 (Q-limit = 15.5 dB), when only first order fiber dispersion is considered. However, including the effects of second and third order fiber dispersion as frequency domain parameters, results in a reduction of the maximum bit rate to 40 Gb/s, while maintaining a Q-factor above the Q-limit under the same transmission distance. Furthermore, we demonstrate that the proposed architecture extends the SMF transmission reach up to 600 km and 480 km, when considering linear and nonlinear effects, respectively. Finally, we show that our proposed 2D-MD SAC-OCDMA system outperforms existing solutions presented in the literature for LR-PON configuration, in terms of both aggregate bit rate and transmission reach.

Comparison of 3D and 2D late gadolinium enhancement magnetic resonance imaging in patients with acute and chronic myocarditis

We compared a fast, single breath-hold three dimensional LGE sequence (3D LGE) with an established two dimensional multi breath-hold sequence (2D LGE) and evaluated image quality and the amount of myocardial fibrosis in patients with acute and chronic myocarditis. 3D LGE and 2D LGE (both spatial resolution 1.5 × 1.5 mm2, slice-thickness 8 mm, field of view 350 × 350 mm2) were acquired in 25 patients with acute myocarditis (mean age 40 ± 18 years, 7 female) and 27 patients with chronic myocarditis (mean age 44 ± 22 years, 9 female) on a 1.5 T MR system. Image quality was evaluated by two independent, blinded readers using a 5-point Likert scale. Total myocardial mass, fibrotic mass and total fibrotic tissue percentage were quantified for both sequences in both groups. There was no significant difference in image quality between 3D und 2D acquisitions in patients with acute (p = 0.8) and chronic (p = 0.5) myocarditis. No significant differences between 3D and 2D acquisitions could be shown for myocardial mass (acute p = 0.2; chronic p = 0.3), fibrous tissue mass (acute p = 0.7; chronic p = 0.1) and total fibrous percentage (acute p = 0.4 and chronic p = 0.2). Inter-observer agreement was substantial to almost perfect. Acquisition time was significantly shorter for 3D LGE (24 ± 5 s) as compared to 2D LGE (350 ± 58 s, p < 0.001). In patients with acute and chronic myocarditis 3D LGE imaging shows equal diagnostic quality compared to standard 2D LGE imaging but with significantly reduced acquisition time.

Volumetric brain tumour detection from MRI using visual saliency.

Medical image processing has become a major player in the world of automatic tumour region detection and is tantamount to the incipient stages of computer aided design. Saliency detection is a crucial application of medical image processing, and serves in its potential aid to medical practitioners by making the affected area stand out in the foreground from the rest of the background image. The algorithm developed here is a new approach to the detection of saliency in a three dimensional multi channel MR image sequence for the glioblastoma multiforme (a form of malignant brain tumour). First we enhance the three channels, FLAIR (Fluid Attenuated Inversion Recovery), T2 and T1C (contrast enhanced with gadolinium) to generate a pseudo coloured RGB image. This is then converted to the CIE L*a*b* color space. Processing on cubes of sizes k = 4, 8, 16, the L*a*b* 3D image is then compressed into volumetric units; each representing the neighbourhood information of the surrounding 64 voxels for k = 4, 512 voxels for k = 8 and 4096 voxels for k = 16, respectively. The spatial distance of these voxels are then compared along the three major axes to generate the novel 3D saliency map of a 3D image, which unambiguously highlights the tumour region. The algorithm operates along the three major axes to maximise the computation efficiency while minimising loss of valuable 3D information. Thus the 3D multichannel MR image saliency detection algorithm is useful in generating a uniform and logistically correct 3D saliency map with pragmatic applicability in Computer Aided Detection (CADe). Assignment of uniform importance to all three axes proves to be an important factor in volumetric processing, which helps in noise reduction and reduces the possibility of compromising essential information. The effectiveness of the algorithm was evaluated over the BRATS MICCAI 2015 dataset having 274 glioma cases, consisting both of high grade and low grade GBM. The results were compared with that of the 2D saliency detection algorithm taken over the entire sequence of brain data. For all comparisons, the Area Under the receiver operator characteristic (ROC) Curve (AUC) has been found to be more than 0.99 ± 0.01 over various tumour types, structures and locations.

A comparison study of voxel based multi- and two-layer ionospheric tomography models over the Indian region using GPS data

Three dimensional multi- and two-layer ionospheric tomographic models have been developed for the Indian region, which may provide an alternative approach for total electron content (TEC) estimation and ionospheric propagation delay correction for user aircraft for Global Positioning System Aided Geo Augmented Navigation (GAGAN). A comparative study has been carried out between multi- and two-layer models with different voxel sizes. Further comparison of two-layer models with different voxel sizes shows that from 0006 to 0017 h UT, the root mean square error (RMSE) of the slant total electron content (STEC) is least for a 10° × 10° voxel size and for the remaining hours the RMSE of the STEC is least for the 15° × 15° voxel size. The main conclusion of the analysis is that the two-layer model performs around 50% better than the multi-layer model over the Indian region.

Aerodynamic Design for Three- Dimensional Multi- lifting Surfaces at Transonic Flow

An aerodynamic design method and corresponding codes are developed for three dimensional multi-lifting surfaces at transonic flow. It is based on the “iterative residual correction” concept that is successfully used for transonic wing design and subsonic multi-lifting surface design. The up wind scheme is introduced into governing equations of multi-lifting surface design method and automatically acted when supersonic flow appears on the surface. A series of interface codes are programmed, including a target- pressure modification tool. Using the improved inverse aerodynamic design code, T A U code and interface codes, the transonic multi-lifting aerodynamic design software system is founded. Two cases of canardwing configuration have been performed to validate the method and codes. The results show that the convergence of analysis/design iteration is very good at higher speed transonic flow.

Multiscale Analysis of Gravity Anomalies on East China Sea and Adjacent Regions

AbstractThe form and depth of sedimentary basement and Moho basement are the main subjects in studies of deep Earth crust of ocean. Because the density difference of the two basements is prominent, which could reach 0.1 g/cm3 and 0.4 g/cm3, the gravity values are suitable to study the basements. However, the gravity anomalies include the whole lithosphere and upper mantle, the decomposition of the gravity field is important to study. Recently we have applied the wavelet analysis to decomposition of gravity field and obtained better results. In order to obtain the gravity anomalies corresponding to the sedimentary and Moho basement, we decomposed the free–air gravity anomalies of East China Sea and adjacent regions by using the two dimensional wavelet decomposition technique. The results show that the fourth order detail of the free‐air gravity anomalies mainly reflects the sedimentary basement and the fourth order approximation of the free–air gravity anomalies reflects the Moho. In this paper, we introduce the method of two dimensional multi–scale decomposition, show the result, and discuss its preliminary interpretation.

116 視点位置検出のための眼球画像の輪郭線抽出法の検討

116 視点位置検出のための眼球画像の輪郭線抽出法の検討

Non-Contact Eye-Gazing Point Detection Technique via Two Dimensional Multi Resolution Analysis.

The purpose of this study is to detect eye-gazing points during driving a wheelchair through the image sequence analysis of video frames. The performances can be measured without restrictions of specific devices such as any accesories and sensors, which were put on a body. Images obtained with three video cameras allow the algorithm to extract four feature points on a face and irises. Their three-dimensional positions were estimated through direct linear transformation (DLT) technique with magnification of a facial image through multi resolution analysis. The direction of a face was estimated via three-dimensional positions of the former, and it defined the facial coordinate. On the other hand, the eye-gazing point was evaluated through three-dimensional positions of the latter. Consequently, Some preliminary results were presented to illustrate the difference in variations with the eye-gazing point between driving a wheelchair and walking.