Biswa Ranjan Swain

Stability and energy aware reverse AODV routing protocol in MANETS

Most of the multipath on demand routing protocols are mobile Adhoc Networks suffer due to frequent changes in the network topology confined network resources such as battery capacity of nodes, security of data packets and scalability of the network. This paper has been proposed a stability and Energy Aware Reverse Adhoc On demand Distance Vector (SEAR-AODV) Routing protocol. This method is a modification of existing Reverse R-AODV routing protocol. It is based on optimization of the existing R-AODV routing protocol by computing the reliability factor (RF) of nodes that includes both energy and rout stability aware metric. SEAR-AODV uses the path with high RF value as the primary path to rout the data packets where as secondary paths are used based on the descending order of their RF values. it uses a new make-before-break route maintenance mechanism. In order to reduce the control overhead due to route recovery. a comparative study by NS2 tool signifies that the proposed protocol SEAR-AODV enhances the packet delivery fraction and reduces both the latency as well as the average consumed energy.

Optimized approach of sobel edge detection technique using Xilinx system generator

In this paper a new method is utilized in which sobel X-Y edge detection combines with Gaussian filter using histogram stretching method. In recent days, the edge detection techniques come to the picture with a very important utilization in medical industry to detect tumors and fractures in the human body[1],[2],[3]. So In this paper we firstly propose a new optimized edge detection technique which is a better edge detection technique so far in our knowledge in terms of improved mean square error(MSE) and picture signal to noise ratio (PSNR) using very limited resources used in the SPARTAN 3A DSP 3400A development platform FPGA kit.

Simulation based algorithm for tracking fish population in unconstrained underwater

Tracking of object in underwater is a emerging idea. There are several type of approaches used for this but they have high computational complexity. But scientist needs to study fish populations underwater in different environmental conditions. In this paper we proposed a simple algorithm for tracking and detecting multi moving fishes. A huge number of fishes can be tracked by comparing its mean in the successive frame of the video. The obtained output states a measurement of the difference of two mean values. The object window contains the matrix of the intensity value. Then this value is transformed into a set of feature vector. Finally the above two set of features is compared in the successive frame for a good match to its nearest locality. The MatLab 8.0 simulation result shows that the proposed method is capable of accurately detecting with high detection rate as compared to existing approaches with noisy and dense environment.

A Simulation based model for bacteria tracking using MTP approach in blood

In this paper, we proposed a method for tracking multi moving bacteria and white blood cell (WBC) using Multi threading parallel (MTP) concept in a microscopic blood cell video. This method is based on continuously adaptive mean shift algorithm using color model which is designed to track multi moving bacteria using multi threading concept by comparing its mean in the successive frame in the video. It is observed that a bacteria can be tracked in the next frame, when the mean shift vector converges. Simulation result shows that the proposed method is capable of detecting multi moving bacteria and WBC quickly as compared to the existing approaches for proper diagnosis.

Multi moving bacteria and WBC tracking using MTP approach for proper diagnosis in blood

In this Paper, we proposed a method for tracking multi moving bacteria and white blood cell (WBC) using Multi threading parallel (MTP) concept in a microscopic blood cell video. This method is based on continuously adaptive mean shift algorithm using color model which is designed to track multi moving bacteria using multi threading concept by comparing its mean in the successive frame in the video. It is observed that bacteria can be tracked in the next frame, when the mean shift vector converges. Simulation result shows that the proposed method is capable of detecting multi moving bacteria and WBC quickly for proper diagnosis.