A Review on Implementation of Image Processing Algorithms using Hardware Software Co-simulation

Edge detection is necessary tool for extraction of information for further image processing operation. Many computer vision application use edge detectors as primary operators before high level image processing. Several algorithms are available for edge detection which makes use of derivative approach. Roberts, Prewitt , sobel, canny are some of the examples of edge detection methods. In this project edge detection algorithms are to be implemented over FPGA board. Proposed architecture gives an alternative by using a graphical user interface which is developed by combining MATLAB, Simulink and XSG tool. Prototype of Application Specific Integrated Circuit [ASIC] can be obtained by FPGA based implementation of edge detection algorithm. Comparative analysis using software and hardware is to be done. Instead of using traditional approach of programming FPGA, Xilinx System Generator [XSG] is used for programming and modeling FPGA. XSG has an integrated design flow to move directly to the bit stream file from simulink design environment which is necessary for programming the FPGA. Advantage of using FPGA is power efficient circuits can be fabricated; it has large memory and superior parallel computing capacity. With use of FPGA, design procedure becomes more flexible. DOI: 10.17762/ijritcc2321-8169.15010

Wear performance optimization of Silicon Nitride using Genetic and simulated annealing algorithm

Replacing damaged joint with the suitable alternative material is a prime requirement in a patient who has arthritis. Generation of wear particles in the artificial joint during action or movement is a serious issue and leads to aseptic loosening of joint. Research in the field of bio-tribology is trying to evaluate materials with minimum wear volume loss so as to extend joint life. Silicon nitride (Si3N4) is non-oxide ceramic suggested as a new alternative for hip/knee joint replacement. Hexagonal Boron Nitride (hBN) is recommended as a solid additive lubricant to improve the wear performance of Si3N4. In this paper, an attempt has been made to evaluate the optimum combination of load and % volume of hBN in Si3N4 to minimize wear volume loss (WVL). The experiments were conducted according to Design of Experiments (DoE)–Taguchi method and a mathematical model is developed. Further, this model is processed with Genetic Algorithm (GA) and Simulated Annealing (SA) to find out the optimum percentage of hBN in Si3N4 to minimize wear volume loss against Alumina (Al2O3) counterface. Taguchi method presents 15 N load and 8% volume of hBN to minimize WVL of Si3N4. While GA and SA optimization offer 11.08 N load, 12.115% volume of hBN and 11.0789 N load, 12.128% volume of hBN respectively to minimize WVL in Si3N4

An Analytical Performance Evaluation on Multiview Clustering Approaches

The concept of machine learning encompasses a wide variety of different approaches, one of which is called clustering. The data points are grouped together in this approach to the problem. Using a clustering method, it is feasible, given a collection of data points, to classify each data point as belonging to a specific group. This can be done if the algorithm is given the collection of data points. In theory, data points that constitute the same group ought to have attributes and characteristics that are equivalent to one another, however data points that belong to other groups ought to have properties and characteristics that are very different from one another. The generation of multiview data is made possible by recent developments in information collecting technologies. The data were collected from à variety of sources and were analysed using a variety of perspectives. The data in question are what are known as multiview data. On a single view, the conventional clustering algorithms are applied. In spite of this, real-world data are complicated and can be clustered in a variety of different ways, depending on how the data are interpreted. In practise, the real-world data are messy. In recent years, Multiview Clustering, often known as MVC, has garnered an increasing amount of attention due to its goal of utilising complimentary and consensus information derived from different points of view. On the other hand, the vast majority of the systems that are currently available only enable the single-clustering scenario, whereby only makes utilization of a single cluster to split the data. This is the case since there is only one cluster accessible. In light of this, it is absolutely necessary to carry out investigation on the multiview data format. The study work is centred on multiview clustering and how well it performs compared to these other strategies

Redundant Wavelet Watermarking using Spread Spectrum Modulation

Spread Spectrum modulation has become a preferred paradigm in many watermarking applications. This paper analyzes the performance of such a blind watermarking scheme under discrete wavelet frame rather than a traditional orthonormal wavelet expansion. The over complete representation offered by the redundant frame facilitates the identification of significant image features via a simple correlation operation across scales. The performance and resiliency of the proposed technique are analyzed against several volumetric distortion sources. The experimental results of this oblivious algorithm illustrate better visual and statistical imperceptibility and robustness compared to the usually critically sampled discrete wavelet transform. This algorithmic architecture utilizes the existing allocated bandwidth in the data transmission channel in a more efficient manner