In this paper we propose an energy efficient video transmission strategy for wireless sensor networks, which combines wavelet-based image decomposition and cooperative communication. The proposed scheme uses the selective decode and forward (SDF) cooperation, so that a relay node collaborates with the source by forwarding only a lower-resolution version of the original video, obtained via discrete wavelet transform (DWT). We show that the proposed SDF-DWT strategy is more energy efficient than non-cooperative single-hop and multi-hop, also outperforming the regular SDF scheme. In addition, we show that our method can achieve the energy efficiency of incremental DF (IDF), without the need of a feedback channel.

Read More...

It is a big challenge to develop routing protocol that can meet different application needs and optimize routing paths according to the topology change in mobile ad hoc networks. The existing work presented two self-adaptive on-demand geographic routing schemes to build efficient paths based on the needs of user applications and adapt to various scenarios for provide efficient and reliable routing. To overcome the impact due to inaccurate local topology knowledge, the topology information is updated at a node in the specific time periods. The on-demand routing mechanism reduces to control overhead made on geographic routing. The route optimization scheme adapts routing path according to the topology changes and actual data traffic requirements. Adaptive parameter setting scheme is introduced to allow each node to determine and adjust the protocol parameter values independently. However, existing work did not address resource parameters such as energy, bandwidth and data loss. The proposal presents and Integrated Resource Adaptive on Demand Geographic Routing (IRA-ODGR) for MANET. The node energy resource is optimized with path energy consumption rate and bandwidth utilization of the path is analysed. Loss rate is reduced in geographic routing with dynamic routes. The simulation conducted to demonstrate IRA-ODGR routing protocols.

Read More...

compressed sensing is a new technique that discards the Shannon Nyquist theorem for reconstructing a signal. It uses very few random measurements that were needed traditionally to recover any signal or image. The need of this technique comes from the fact that most of the information is provided by few of the signal coefficients, then why do we have to acquire all the data if it is thrown away without being used. A number of review articles and research papers have been published in this area. But with the increasing interest of practitioners in this emerging field it is mandatory to take a fresh look at this method and its implementations. The main aim of this paper is to review the compressive sensing theory and its applications.

Read More...

The standard back-propagation algorithm is one of the most widely used algorithm for training feed-forward neural networks. One major drawback of this algorithm is it might fall into local minima and slow convergence rate. Natural gradient descent is principal method for solving nonlinear function is presented and is combined with the modified back-propagation algorithm yielding a new fast training multilayer algorithm. This paper describes new approach to natural gradient learning in which the number of parameters necessary is much smaller than the natural gradient algorithm. This new method exploits the algebraic structure of the parameter space to reduce the space and time complexity of algorithm and improve its performance.

Read More...

Medical field has greatly benefited from automation that can outperform even the most skilled human operators in certain tasks. When the patient is not able to breathe properly by his own, ventilators are used to assist patient in breathing for long or short period, mainly in hospitals. A nurse is required to maintain the patient‟s ventilator functioning periodically. In this paper, we have tried to monitor medical ventilators functioning with PC, in control room using SCADA (supervisory control and data acquisition). SCADA is a type of industrial control system, which is computer controlled systems that monitors and controls the industrial processes that exist in the physical world. Presented paper describes the biomedical implementation of SCADA. All the ventilators used in hospitals can be simulated with a computer, which will display the value of peep pressure, respiration rate, inspiratory pressure etc. Any irregularity or problem can be detected and treatment can be given to that particular patient. This will reduce the human efforts and time.

Read More...

Visual prior from generic real-world images study to represent that objects in a scene. The existing work presented online tracking algorithm to transfers visual prior learned offline for online object tracking. To learn complete dictionary to represent visual prior with collection of real world images. Prior knowledge of objects is generic and training image set does not contain any observation of target object. Transfer learned visual prior to construct object representation using Sparse coding and Multiscale max pooling. Linear classifier is learned online to distinguish target from background and also to identify target and background appearance variations over time. Tracking is carried out within Bayesian inference framework and learned classifier is used to construct observation model. Particle filter is used to estimate the tracking result sequentially however, unable to work efficiently in noisy scenes. Time sift variance were not appropriated to track target object with observer value to prior information of object structure. Proposal HMM based kalman filter to improve online target tracking in noisy sequential image frames. The covariance vector is measured to identify noisy scenes. Discrete time steps are evaluated for identifying target object with background separation. Experiment conducted on challenging sequences of scene. To evaluate the performance of object tracking algorithm in terms of tracking success rate, Centre location error, Number of scenes, Learning object sizes, and Latency for tracking.

Read More...

There are a lot of image segmentation techniques that try to differentiate between backgrounds and object pixels but many of them fail to discriminate between different objects that are close to each other, e.g. low contrast between foreground and background regions increase the difficulty for segmenting images. So we introduced the Chan-Vese active contours model for image segmentation to detect the objects in given image, which is built based on techniques of curve evolution and level set method. The Chan-Vese model is a special case of Mumford-Shah functional for segmentation and level sets. It differs from other active contour models in that it is not edge dependent, therefore it is more capable of detecting objects whose boundaries may not be defined by a gradient. Finally, we developed code in Matlab 7.8 for solving resulting Partial differential equation numerically by the finite differences schemes on pixel-by-pixel domain.

Read More...

Image plays a vital role in image processing. In Image processing Depth of Field is to segment the relevant object from an Image. Depth of Field is the space between the near and extreme objects in a scene. The objective of this work is to segment the image using Low Depth of Field .Unsupervised segmentation is used to find low depth of field image. Saliency map and curve evaluation method is created and initialized for the image. Energy map have been employed so as to bring the desired result. Lipschitz function is used to generate the mathematical view of representation. Various Iteration methods have shown the graphical representation of an image. The Segmented results have shown the Object detection in an image.

Read More...

Computer forensic uses many techniques for investigating and getting evidence regarding activity of computer, which is acceptable in court of law. The need of digital evidence is becoming crucial. For this purpose Computer forensic science is the application of science to find legal evidence from computers and other storage devices, so that truth comes out. The goal of forensic science is to provide valid and trustworthy information to investigator and the court. In old days forensic science was limited to fingerprint comparison, trace evidence, tool marks, toxicology and serology. But now it is expanded by including DNA analysis, explosion analysis, risky material analysis and audio/video analysis. That‟s how forensic science has become powerful weapon to investigate and control crimes. The evidence which is provided by forensic science has become "true fact of life", because it tells about incident step by step. Evidence related to theft, extortion, hacking, even murder has been exposed with the help of forensic science. This new technology has become foremost part in law sanction circles. In today‟s world awareness of applicable laws in practice of computer forensic is necessary for all type of organizations. Like for network administrators and security staff needs to know all issues regarding to computer forensics. Employees of corporate governance, legal departments or IT should be known about all aspect of computer forensics. Forensics required employees with balanced combination of technical skill, legal acumen and ethical conduct who is known as computer forensic specialist. Cyber-crime rates are increasing and computer forensic science has power to control these cyber-crimes. The utilization of personal computer is very wide, data exchange is more than ever before and high-tech crimes are on increase. That‟s why we need to have computer forensic service to get successful prosecutions in court of low. Main purpose of this paper is to conduct a little investigation on computer forensic science or computer forensics.

Read More...

The present study is about the anti-microbial activity of the bacteriocin producing lactobacilli and optimization of bacteriocin production. Bacteriocin was extracted by solvent extraction with chloroform and the antimicrobial activity was tested against 5 different pathogens by agar spotting method. Optimization of bacteriocin production was done for 4 different parameters such as pH, Temperature, Carbon source and Nitrogen source and the anti-microbial activity was tested against the following 5 different pathogens and the results were observed and diameter of the zone of inhibition was measured and tabulated. From the results of the study it was found that bacteriocin produced from lactobacilli has good antimicrobial activity.

Read More...

A new type of image similarity method is proposed, which created automatically by composing small fragments of given secret image in mosaic form in the target image .The mosaic image is yielded by dividing the secret image into fragments and transforming the colour characteristics of secret image to that of target image. Skilful techniques are used in the colour transformation process so that secret image may be recovered nearly lossless.

Read More...

Magnetic confinement of plasma can be achieved using a device Tokamak. Concept of Tokamak confinement is also been tried to develop a fusion reactor. Reactor environment is of high hostile for human intervention due to radiation from activated atoms. For any kind of maintenance works Remote operation is necessary. An attempt was made to arrive at a concept of using articulated inspection arm to check the components if any damage or replacement required during shutdown operation of reactor machine. Proof of concept towards Design and development of articulated inspection arm for Torus Vessel was carried out & a robot having multi link joint with a camera mounted on the end point and also an arm having three degrees of freedom was attempted. The concept was materialized developing an articulated inspection robotic arm.

Read More...