Recognition of high resolution fingerprint images
Fingerprint recognition is one of the most prominent biometric identification techniques. The features of fingerprint are broadly classified into three categories namely level 1, level 2 and level 3 features. In order to increase the recognition rate here the hierarchical matching technique is used which allows us to use all levels of features hierarchically. The level 3 features can be observed only in 1000 dpi images. So the matching is performed on a 1000 dpi fingerprint database captured using Hamster IV fingerprint scanner. At the first level of hierarchical matching the agreement between two orientation images is tested using dot product of the images. If an image is accepted at the first level it is brought to the second level of matching where minutiae details are tested. If an image crosses this stage as accepted then the decision will be taken as genuine otherwise the image will be given to the third level. The third level extracts the level 3 features such as pores and ridge contour points using Dynamic Anisotropic Pore Model (DAPM) and Mexican hat wavelet transform respectively. For each matched minutiae the pores and ridge contour points within the associated region of that minutiae will be matched. Based on the third level of matching a person is accepted as genuine or rejected as imposter.
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Residential Intrusion Detection System Using Face Recognition
Lifestyle in the modern society along with human behavior and thinking is changing dramatically with the advancement of technology, and the concept of a simple home is changing into a smart home. Home Security has been a major issue where crime is increasing and everybody wants to take proper measure to prevent intrusion, besides homes the system is also implemented in business premises and office. This project is residential intrusion detection and it detects the face by using image processing
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Analyzing download time performance of university websites in India
The download time of website depends on various web components such as multimedia size, document size, program size and so on. The main objective of this paper is to Analyze Download time of University Websites in India and evaluating the quality of Website Download time Performance based on Download time Performance metric. The Download time of websites is measured in various grades viz., A, B, C, D, E, F etc., A 10 point metric for Download time performance is investigated based on Download time performance grades.
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Comsol simulation of electrokinetic valve for the separation of ions
Separation of ions is a major problem in chemical industries. There are several techniques to separate ions, one of the technique is the use of electrokinetic valve. Electrokinetic valve is used to separate ions by applying external electric field. Earlier it is designed using CAD software. In this paper we present an approach of designing electrokinetic valve using COMSOL multiphysics in a miniature way.
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Prime number generation using genetic algorithm
In the modern cryptography, the problem of the generation of large primes is considered as an important issue to implement public key crypto-scheme such as RSA and so on. Since a great amount of computational resources is generally required to generate a large prime number, it takes considerable amount of resource especially in embedded systems. In general, the prime number generation is started from the random number generation. If the generated random number is passed a specified probabilistic primality test, the random number is tentatively considered as a prime number and applied to a public key crypto-system. In many primality tests, a number of modular exponentiations are usually required. Hence these algorithms are considerably slow. Here we are introducing a new prime generation technique using GA which can be used to generate large primes in more efficient way.
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Student Identification Using Biometric
Bio-metric identification systems are widely used for unique identification of humans mainly is verification and identification .It is used as a form of identity access management and access control. Fingerprint identification is one of the best biometric technique. The biometric fingerprints identification are secure to use and mainly unique for every person and do not change in one’s lifetime. This paper is to identify each and every student of the department as well as the college.
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Implementation of Efficient Signature Scheme for Leakage Free Dissemination of XML Content using Structure Based Routing
Nowadays security has always been an important issue in the business world to ensure the integrity of content and transactions, to maintain confidentiality and privacy, and to make sure information is disseminated appropriately. But while dealing with contents encoded in XML, the hierarchical tree structured data have different confidentiality and integrity for different portions of the same content. Thus need dissemination approach specifically tailored to XML that addresses the issues of efficiency and scalability must however be provided by assuring at the same time security of contents and privacy of the parties acquiring and disseminating contents. The main objective is to provide solution to above problem using structural properties of tree based data model (such as XML document) and Document Object Model (DOM). This approach is based on notion of Encrypted Post Order Numbers (EPON) which is based on tree traversals and is defined using a random notation of such traversal number. It facilitates efficient dissemination of selected portion of content. By using structure based routing (SBR) scheme that prevents information leakage and assures that delivered content to user according to access control policies. The structure based routing framework facilitates the dissemination of contents with varying degrees of confidentiality and integrity in a network.
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Operation and control of micro sources in Island mode of a Microgrid
In the country like India where population is increasing at a rapid rate the electrical power demand has become a great problem. Unfortunately the conventional energy resources are limited, cause greenhouse emissions and are expected to increase in costs due to an increase in the demand. Recently, the new concept of MicroGrid has been emerging on distribution network for integration of micro generation in low voltage network and to increase the reliability of supply. A microgrid is a cluster of micro generators, loads, storage devices, control devices and a low voltage distribution network functioning in a coordinated manner. The microgrid can operate in two different modes: interconnected or emergency. In first mode the microgrid is connected with the conventional low voltage distribution network for importing or exporting electricity. In emergency mode the microgrid is isolated (islanded) with the help of control devices from the distribution network and uses local micro-generators, changing from power control to frequency control. Most of the micro sources installed in a microgrid cannot be connected directly to the electrical network therefore; power electronics interfaces (dc/ac or ac/dc/ac) are required. Thus, the inverter control is also a challenge for smooth and reliable operation of a smart microgrid. This paper describes microgrid operation in various modes and various control strategies adopted.
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A Study of Improving the Energy Efficiency in Distributed Network systems Using Computer Peripherals
The Large- Scale Computing and network systems consume more amount of power and computer components like Mother Board, Processor, RAM, Hard Disk, VGA (Video Graphics Adapter), AGP (Accelerated Graphics Port), Network ports, data centers and supercomputers. Most of the places like schools, colleges, and IT Industries people work with computer. Day by day the energy consumed by these computer peripherals all over the world is high. Trying to reduce these high energy consumption a study and survey techniques have been analyzed. This survey techniques and solutions will improve the energy efficiency in computing devices and network resources. This method discusses to evaluate the maximum power consumed by the resources and explains the techniques that operate at distributing systems, trying to allocate resource for scheduling, network management. This study aims about the art of energy efficiency in computing resources and network components.
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A survey paper on bias corrected fuzzy based image clustering in brain MRI
Magnetic resonance Image (MRI) is a medical image method use in radiology to visualize internal body structures like tissues. MRI method provides high-quality contrast effect to visual tissues of brain and MRI contrast is enhancing appearance of tumors in brain. In this survey compared the CLIC, EM, AFCM, Bias Field Estimation, SFKFCM, MFCM and FLGMM methods for accurate brain segmentation in MRI images. CLIC method to evaluate metric tissue classification and estimate bias field minimizing energy, optimal bias field derived smoothness of CLIC method. It’s applied for fully automated applications. AFCM applied on corrupted images in reality accurate in classification and partial volume effect. MR data corrupted truth brightness variation in each component. AFCM implementation is faster than other methods one major problem in AFCM method is to look for clusters of the same shape, size and increased complexity. Bias corrected FCM method with spatial neighborhood regularization period and its time taking; lacks robustness to noise is main problem of the method. In GKFCM method with a spatial bias correlation can automatically learn parameters by prototype driven learning scheme and this method is effective more robust to noise. SFKFCM method for segmenting brain MRI images and correcting spurious variations, to improve the separability of observed data, fast clustering scheme improve speed up process and execution time is reduced improved clustering results. MFCM for adaptive segmentation and intensity correlation of MR images and automation available for the segmentation of MR images into tissues classes correcting interscan intensity inhomogenetics. MFCM leads to increased improvement in quality of 3D brain structures and visualization. GMM voxel intensities in each target region, its lack of taking spatial information and uncertainty data may produce poor segmentation result. To overcome problem in segmentation FGMM concept is proposed for uncertainty data and parameter quality improvement. The integration of the weighted GMM energy functions in the entire image and uses a truncated Gaussian kernel function to incorporate spatial constraints into local GMM employ the fuzzy membership function to balance each GMM segmentation process. FGMM reduced noise, low contrast, bias field and improved segmentation result compared with all other methods proposed by previous researches.
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