Comparative Analysis and Evaluation of Image inpainting Algorithms

Image inpainting refers to the task of filling in the missing or damaged regions of an image in an undetectable manner. There are a large variety of image inpainting algorithms existing in the literature. They can broadly be grouped into two categories such as Partial Differential Equation (PDE) based algorithms and Exemplar based Texture synthesis algorithms. However no recent study has been undertaken for a comparative evaluation of these algorithms. In this paper, we are comparing two different types of image inpainting algorithms. The algorithms analyzed are Marcelo Bertalmio’s PDE based inpainting algorithm and Zhaolin Lu et al’s exemplar based Image inpainting algorithm.Both theoretical analysis and experiments have made to analyze the results of these image inpainting algorithms on the basis of both qualitative and quantitative way. Keywords:Image inpainting, Exemplar based, Texture synthesis, Partial Differential Equation (PDE)

Combined Structure and Texture Image Inpainting Algorithm for Natural Scene Image Completion

Image inpainting or image completion refers to the task of filling in the missing or damaged regions of an image in a visually plausible way. Many works on this subject have been proposed these recent years. We present a hybrid method for completion of images of natural scenery, where the removal of a foreground object creates a hole in the image. The basic idea is to decompose the original image into a structure and a texture image. Reconstruction of each image is performed separately. The missing information in the structure component is reconstructed using a structure inpainting algorithm, while the texture component is repaired by an improved exemplar based texture synthesis technique. Taking advantage of both the structure inpainting methods and texture synthesis techniques, we designed an effective image reconstruction method. A comparison with some existing methods on different natural images shows the merits of our proposed approach in providing high quality inpainted images. Keywords: Image inpainting, Decomposition method, Structure inpainting, Exemplar based, Texture synthesi

Document Image Binarization Using Post Processing Method

Binarization is the preliminary process of Document Image Analysis and Processing. Image binarization is performed through Local and Global threshold methods. In this paper local thresholding method Nilblack method with post processing was implemented. The Nilblack algorithm was implemented using Matlab and tested with a sample of ground tooth images selected from TOBACCO research database

ENHANCE FAIR ROUTING WITH RESOURCE FLEXIBLE NODE ALLOCATION IN WIRELESS SENSOR NETWORKS

Wireless sensor network is a network composed of a large number of sensor nodes with limited radio capabilities and one or a few sinks that collect data from sensor nodes. Sensor nodes are powered by small batteries, hence, the energy consumption in operating a WSN should be as low as possible. The wireless sensor network present all sensor nodes generate an equal amount of data packets in a WSN, nodes around a sink have to relay more packets and tend to die earlier than other nodes because the energy consumption of sensor nodes is almost completely dominated by data communication rather than by sensing and processing. Hence, the whole network lifetime can be prolonged by balancing the communication load at heavily loaded nodes around a sink. This problem is called the energy hole problem and is one of the most important issues for WSNs. Existing system analysis the heterogeneity of networks and a fair cooperative routing method, to avoid unfair improvement only on certain networks and to introduce one or a few shared nodes that can use multiple channels to relay data packets

Cronobacter sakazakii infection alters serotonin transporter and improved fear memory retention in the rat

It is well established that Cronobacter sakazakii infection cause septicemia, necrotizingenterocolitis (NEC) and meningitis. In the present study, we tested whether the C. sakazakii infection alter the learning and memory through serotonin transporter (SERT). To investigate the possible effect on SERT, on postnatal day (PND)-15, wistar rat pups were administered with single dose of C. sakazakii culture (Infected group: IF; 107 CFU) or 100μL of Luria-Bertani broth (LB; Medium Control: MC) or without any treatment (Naïve control: NC). All the individuals were subjected to passive avoidance test on PND-30 to test their fear memory. We show that single dose of C. sakazakii infection improved fear memory retention. Subsequently, we show that C. sakazakii infection induced the activation of Toll-like receptor-3 (TLR-3) and heat-shock proteins-90 (Hsp-90). On the other hand, level of serotonin (5-HT) and SERT protein was down-regulated. Furthermore, we show that C. sakazakii infection up-regulate microRNA (miR)-16 expression. The observed results highlight that C. sakazakii infections was responsible for improved fear memory retention and may have reduced the level of SERT protein, which is possibly associated with the interaction of up-regulated Hsp-90 with SERT protein or miR-16 with SERT mRNA. Taken together, observed results suggest that C. sakazakkii infection alter the fear memory possibly through SERT. Hence, this model may be effective to test the C. sakazakii infection induced changes in synaptic plasticity through SERT and effect of other pharmacological agents against pathogen induced memory disorder

Design of Multiple Ontology Based Agro Knowledge Mining Model

Farming is regarded as a major industry in India, accounting for 17% of the country's GDP growth. Agriculture employs 60% of the population hence it is considered an important sector in India. The important factors for agriculture are pest management, disease prevention, irrigation management, soil mineral composition, crop management, location, and the season in which the crop is grown. Hence all this information along with the techniques are well known only by the experienced farmers. Hence it is important to create an agro knowledge management system. As a result, this work makes an attempt to develop a multiple ontology-based agro knowledge management system. The designed system consists of agriculture information related to attributes of soil mineral, moisture, season, location, crop type, and temperature. It consists of multiple ontologies such as soil ontology, crop ontology, location ontology, and crop season ontology to provide agronomy knowledge. Soil ontology is premeditated to classify the soil type in a hierarchical order while crop ontology classifies the crop type, location ontology classifies locations suitable for different crop types and finally, crop season ontology classifies the season that is suitable for different crops. A rule base is built to develop the knowledge base and to validate the truthfulness of the knowledge base. Visualization of a knowledge base is carried out for better understanding and decision-making

Systems approaches and algorithms for discovery of combinatorial therapies

Effective therapy of complex diseases requires control of highly non-linear complex networks that remain incompletely characterized. In particular, drug intervention can be seen as control of signaling in cellular networks. Identification of control parameters presents an extreme challenge due to the combinatorial explosion of control possibilities in combination therapy and to the incomplete knowledge of the systems biology of cells. In this review paper we describe the main current and proposed approaches to the design of combinatorial therapies, including the empirical methods used now by clinicians and alternative approaches suggested recently by several authors. New approaches for designing combinations arising from systems biology are described. We discuss in special detail the design of algorithms that identify optimal control parameters in cellular networks based on a quantitative characterization of control landscapes, maximizing utilization of incomplete knowledge of the state and structure of intracellular networks. The use of new technology for high-throughput measurements is key to these new approaches to combination therapy and essential for the characterization of control landscapes and implementation of the algorithms. Combinatorial optimization in medical therapy is also compared with the combinatorial optimization of engineering and materials science and similarities and differences are delineated.Comment: 25 page

Heat and mass transmission of an Oldroyd-B nanofluid flow through a stratified medium with swimming of motile gyrotactic microorganisms and nanoparticles

This paper focuses on the research of motile microorganism rates in the bioconvective Oldroyd-B nanoliquid flow over a vertical stretching sheet with mixed convection and inclined magnetic field. Additionally, interesting characteristics of thermophoresis, Brownian motion, viscous dissipation, Joule heating, and stratification are examined. Similarity transformations are employed to reduce the mathematical model to higher-order ODE. The convergent serious solution is applied to solve the nonlinear differential system. The analysis of temperature, velocity, motile microorganisms’ density, and nanoparticle concentration are represented through graphs. Local Nusselt number, density number of motile microorganisms, and Sherwood number are examined via contour plots

Magneto Transport of high TCR (temperature coefficient of resistance) La2/3Ca1/3MnO3: Ag Polycrystalline Composites

We report the synthesis, (micro)structural, magneto-transport and magnetization of polycrystalline La2/3Ca1/3MnO3:Agx composites with x = 0.0, 0.1, 0.2, 0.3 and 0.4. The temperature coefficient of resistance (TCR) near ferromagnetic (FM) transition is increased significantly with addition of Ag. The FM transition temperature (TFM) is also increased slightly with Ag addition. Magneto-transport measurements revealed that magneto-resistance MR is found to be maximum near TFM. Further the increased MR of up to 60% is seen above 300 K for higher silver added samples in an applied field of 7 Tesla. Sharp TCR is seen near TFM with highest value of up to 15 % for Ag (0.4) sample, which is an order of magnitude higher than as for present pristine sample and best value yet reported for any polycrystalline LCMO compound. Increased TCR, TFM and significant above room temperature MR of La2/3Ca1/3MnO3:Agx composites is explained on the basis of improved grains size and connectivity with silver addition in the matrix. Better coupled FM domains and nearly conducting grain boundaries give rise to improved physical properties of the La2/3Ca1/3MnO3 manganites.Comment: 16 pages Text + Figs. ACCEPTED: Solid State Communications (Sept. 2006