Volume 3 Number 1 June 2013


A Secure Model and Algorithms for Cloud Computing based on Multicloud Service Providers
Ashutosh Satapathy, J. Chandrakanta Badajena

Abstract: In modern computing environment, using cloud computing mechanism, cloud service provider provides its internal storages for storing client's data and installing firewall, ips/ids to protect against attacks. To achieve data privacy protection one common method used is storage of data in encrypted format. If a cloud service provider is responsible for all services (authentication, encryption/decryption, storage and auditing) then high level administrators may obtain user id, password, encrypted data and decryption keys which cause a risk for the unauthorized disclosure of the user data. This model proposes a secure cloud computing model based on separating the storage service from authentication, encryption/ decryption and auditing services. In addition, the party operates on storage must store encrypted data and the party operates on authentication, encryption/ decryption and auditing services must delete all data upon computation complete i.e. One cloud service provider is responsible for storage and the other one is responsible for authentication, encryption/ decryption and auditing services. At last the cloud service providers should sign multi-party service level agreement to establish cooperation model for providing common services to clients.


QR- DWT Code Image Steganography
M Ramesh, G Prabakaran, R Bhavani

Abstract: Steganography is the art and science of writing hidden messages in such a way that no one apart from the sender and intended recipient even realizes there is a hidden message. The proposed algorithm is a hybrid Steganography scheme based on Quick Response (QR-code) and Discrete Wavelet Transform (DWT). This technique includes encoding and decoding operation in frequency domain. The text message is hidden in the QR-code image. The QR code image is hidden into the Discrete Wavelet Transform. This technique performed well and additional security given to the information. The performance evaluation done by using statistical parameters. This work was compared to other techniques. The proposed method achieved high security and more imperceptibility.


Efficient and Contorlled Sharing of Privacy Data in Social Network
T H Theepigaa, A Bhuvaneswari

Abstract: Online social Networks (OSNs) have become a successful portal for millions of Internet users. These OSNs offer attractive means for digital social interactions and information sharing, but also raise a number of security and privacy issues. While OSNs allow users to restrict access to shared data, they currently do not provide any mechanism to enforce the privacy over data associated with multiple users. To share the private data and content our analysis presents an approach to enable the protection of shared data associated with multiple users in social networks. We formulate an access control model to capture the essence of multiparty authorization requirements, along with a multiparty policy specification scheme and enforcement mechanism. The access control model allows us to overcome the disadvantages of existing system and perform various analysis tasks on sharing privacy data and selection strategies using the multiparty access control Framework.


Gamma Correction Technique Based Feature Extraction for Face Recognition System
B Vinothkumar, P Kumar

Abstract: One of the most important challenges for practical face recognition systems is to make recognition more reliable under uncontrolled lighting conditions. We tackle this by using novel illumination-insensitive preprocessing method. The proposed face recognition system consists of a gamma correction, a preprocessing stage, a hybrid Fourier-based facial feature extraction, and Principal Component Linear Discriminant Analysis (PCLDA). Gamma Correction is a nonlinear gray-level transformation that replaces gray-level I with Iγ (for γ > 0), where γ is a user-defined parameter. In the preprocessing stage, an “Integral Normalized Gradient Image”, (INGI) is obtained by transform a face image into an illumination-insensitive image. The effect of illumination gets reduced in the INGI by normalizing and integrating the smoothed gradients of a facial image. Using frequency band model selection the hybrid Fourier features are extracted from three different Fourier domains in different frequency bandwidths and further by adding PCLDA the robustness of the system gets improved. In face recognition, it is not possible to process with the entire extracted features, hence the dimension of the feature vectors has to be reduced. In this paper, this is done by using the linear method called PCLDA. The proposed system using the Yale B data set which is having a 2-D face images under various environmental variations such as illumination changes and expression changes.


Multi-camera Image Quality Measure in Video Images using Sub-pixel Allocation Algorithm
A Niranjil Kumar, C Sureshkumar

Abstract: Multi-camera applications are numerous and each application has its specific means of acquisition representation and display. The quality of the perceived multi view video image is dependent on the means of presentation. The most of the fundamental problem in MIQM (Multi-camera Image Quality Measure) is finding the image quality by reducing the distortions. Distortions in multi-camera system can be classified into geometric and photometric distortions. Geometric distortion in multi-camera system is structural disparity such as discontinuity and misalignment in the observed image due to geometric error. Geometric error can occur during mapping which may include rotation and translation. Photometric distortion in single camera is degradation in perceptual feature that are known to attract visual attention such as noise blur and blocking artifacts. MIQM is comprised of three index measures; luminance and contrast index, spatial motion index and edge-based structural index. We propose multi-camera image quality measure is a combination of these three index measure that captures the impact of distortions on multi view perception. The measure was designed to capture the visual effects of artifacts introduced at the acquisition and pre compositing process to predict the composed image quality. By reducing the distortions the quality of video image is improved by sub-pixel allocation algorithm.


Analysis of Effects of Feature Selection to ImproveModels Performance during Automated Evaluation of Descriptive Answers through Sequential Minimal Optimization
C Sunil Kumar, R J Rama Sree

Abstract: In this paper, we applied feature selection as a technique to eliminate the problem of huge number of features in text classification. We quantitatively analyzed the usefulness of various syntactical and semantic features of the text with regards to models’ performance. Based on the results we derived general principles to apply during auto evaluation of descriptive answers.


A Reconfigurable On-Chip Multichannel Data Acquisition and Processing (DAQP) System with Online Monitoring Using Network Control Module
S Velmurugan, C Rajasekaran

Abstract: The data acquisition and processing architecture covers the most demanding applications in continuous patient monitoring for chronic diseases in medical field and also measuring the signals from industrial plants. The multichannel data acquisition is essential for acquiring and monitoring the various biomedical signals from biomedical sensors or signals from industrial sensors. The problem is that the data storage, hardware size and remote monitoring of the sensed signal/data, so the multichannel data obtained is processed at runtime and stored in an external storage for future reference and remote monitoring of the system is done using Ethernet/Wi-Fi supportive network control module. The method of implementing the proposed design is the system on-chip via field programmable gate array (SoC-FPGA) to reduce the hardware size and for memory size. The Soc-FPGA attains high resolution and real time processing of data acquisition and signal processing. A four channel data acquisition and processing (DAQP) was designed, developed using the Lab VIEW graphical programming. NI DAQ and NI FPGA module is used to test and implement the design for real time. The module was designed in order to provide high accuracy, storage and portability.


Design of 2x2 Mimo OFDM Architecture for Fixed WIMAX
S Ganeshkumar, S Venkatesh

Abstract: Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing technology is an advanced transmission technique for wireless communication systems. In this paper, the 64 point pipeline FFT/IFFT processor is introduced for efficient implementation of OFDM architecture. The IFFT processor is used to modulate the subcarrier in transmitter section and FFT processor demodulate the subcarrier in receiver section in the architecture. Our design adopts a single-path delay feedback style requiring less memory space and reconfigurable complex constant multiplier and bit parallel multiplier used in pipeline FFT/IFFT processor, instead of using ROM’s to store twiddle factors that consuming lower power. The design of ROM-less FFT/IFFT processor is applied to OFDM architecture with different encoding and decoding techniques analysis in the IEEE 802.16d communication standard. The result shows overall architecture design using the ROM-less FFT/IFFT processor with convolutional encoding and decoding gives efficient power, area and timing specifications considerably.


Enhanced Binary Small World Optimization Algorithm for High Dimensional Datasets
K Thangadurai, N Kurinjivendhan

Abstract: Large scale databases with high dimensional datasets can be mined and used for making decisions which may be unknown information but effective and will be used in the related fields like bio-informatics, medical, business, etc. Clustering is an unsupervised method that creates group of objects or clusters such that objects in the same group are very similar and objects in different group are very distinct. It allows users to analyze data from many different dimensions and categorize it, and summarize the relationships. Technically, binary small world optimization algorithm (BSWOA) is newly implied technique. In this paper, we review and compare these clustering algorithms to identify their efficiency and differences among them.


Fourier Transform and Image Processing in Automated Fabric Defect Inspection System
G M Nasira, P Banumathi

Abstract- Automated fabric inspection system is important to prevent delivering of inferior quality fabric and designed to increase the accuracy, consistency and speed of defect detection in fabric manufacturing process to reduce labor costs, improve product quality and increase manufacturing efficiency. Fabric inspection is still carried out offline and manually by humans with many drawbacks such as tiredness, boredom and inattentiveness. The continuous development in computer technology introduces the online fabric inspection system based on image processing as an effective alternative of offline inspection system. This paper proposes an effective and accurate approach to automatic fabric inspection system. The defect free fabric has a periodic regular structure, the occurrence of a defect in the fabric breaks the regular structure. Therefore the fabric defects can be detected by monitoring fabric structure. The Fabric inspection system first acquires high resolution, high contrast and minimum noise of image with suitable format. In this paper Fast Fourier transform technique and cross correlation techniques are implemented on plain fabric to examine the structure regularity features of the image.