IJCSIT - MOST CITED - Top 10 PAPERS
1. Diagonal Based Feature Extraction for Handwritten Alphabets Recognition System Using Neural Network
J.Pradeep, E.Srinivasan and S.Himavathi
February 2011 | Cited by 160
An off-line handwritten alphabetical character recognition system using multilayer feed forward neural network is described in the paper. A new method, called, diagonal based feature extraction is introduced for extracting the features of the handwritten alphabets. Fifty data sets, each containing 26 alphabets written by various people, are used for training the neural network and 570 different handwritten alphabetical characters are used for testing. The proposed recognition system performs quite well yielding higher levels of recognition accuracy compared to the systems employing the conventional horizontal and vertical methods of feature extraction. This system will be suitable for converting handwritten documents into structural text form and recognizing handwritten names.2. A Novel Technique for Image Steganography Based on Block-DCT and Huffman Encoding
A.Nag, S.Biswas, D.Sarkar and P.P.Sarka
June 2010 | Cited by 159
Image steganography is the art of hiding information into a cover image. This paper presents a novel technique for Image steganography based on Block-DCT, where DCT is used to transform original image (cover image) blocks from spatial domain to frequency domain. Firstly a gray level image of size M � N is divided into no joint 8 � 8 blocks and a two dimensional Discrete Cosine Transform(2-d DCT) is performed on each of the P = MN / 64 blocks. Then Huffman encoding is also performed on the secret messages/images before embedding and each bit of Huffman code of secret message/image is embedded in the frequency domain by altering the least significant bit of each of the DCT coefficients of cover image blocks. The experimental results show that the algorithm has a high capacity and a good invisibility. Moreover PSNR of cover image with stego-image shows the better results in comparison with other existing steganography approaches. Furthermore, satisfactory security is maintained since the secret message/image cannot be extracted without knowing decoding rules and Huffman table.3. Edge Detection Techniques for Image Segmentation
Muthukrishnan.R and M.Radha
June 2011 | Cited by 114
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has received much awareness of researchers. In image interpretation the partition of the image into object and background is a severe step. Segmentation separates an image into its component regions or objects. Image segmentation t needs to segment the object from the background to read the image properly and identify the content of the image carefully. In this context, edge detection is a fundamental tool for image segmentation. In this paper an attempt is made to study the performance of most commonly used edge detection techniques for image segmentation and also the comparison of these techniques is carried out with an experiment by using MATLAB software.4. Hybrid GPS-GSM Localization of Automobile Tracking System
Mohammad A. Al-Khedher
December 2011 | Cited by 110
An integrated GPS-GSM system is proposed to track vehicles using Google Earth application. The remote module has a GPS mounted on the moving vehicle to identify its current position, and to be transferred by GSM with other parameters acquired by the automobile�s data port as an SMS to a recipient station. The received GPS coordinates are filtered using a Kalman filter to enhance the accuracy of measured position. After data processing, Google Earth application is used to view the current location and status of each vehicle. This goal of this system is to manage fleet, police automobiles distribution and car theft cautions.5. Segmentation and Object Recognition Using Edge Detection Techniques
Y.Ramadevi, T.Sridevi, B.Poornima and B.Kalyani
December 2010 | Cited by 102
Image segmentation is to partition an image into meaningful regions with respect to a particular application. Object recognition is the task of finding a given object in an image or video sequence. In this paper, interaction between image segmentation (using different edge detection methods) and object recognition are discussed. Edge detection methods such as Sobel, Prewitt, Roberts, Canny, Laplacian of Guassian(LoG) are used for segmenting the image. Expectation-Maximization (EM) algorithm, OSTU and Genetic algorithms were used to demonstrate the synergy between the segmented images and object recognition.6. Security Threats on Cloud Computing Vulnerabilities
Te-Shun Chou
June 2013 | Cited by 98
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a �realistic� network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition, countermeasures to cloud security breaches are presented.7. Common Phases of Computer Forensics Investigation Models
Yunus Yusoff, Roslan Ismail and Zainuddin Hassan
June 2011 | Cited by 96
The increasing criminal activities using digital information as the means or targets warrant for a structured manner in dealing with them. Since 1984 when a formalized process been introduced, a great number of new and improved computer forensic investigation processes have been developed. In this paper, we reviewed a few selected investigation processes that have been produced throughout the years and then identified the commonly shared processes. Hopefully, with the identification of the commonly shard process, it would make it easier for the new users to understand the processes and also to serve as the basic underlying concept for the development of a new set of processes. Based on the commonly shared processes, we proposed a generic computer forensics investigation model, known as GCFIM.8. Performance Analysis of Wind Turbine as a Distributed Generation Unit in Distribution System
Ramadoni Syahputra, Imam Robandi and Mochamad Ashar
June 2014 | Cited by 75
In this paper, the performance analysis of wind turbine as a distributed generation unit is presented. In this study a model of wind power is driven by an induction machine. Wind power that is distributed generation is capable of supplying power to ac power distribution network. Wind power generation system is modeled and simulated using Matlab Simulink software such that it can be suitable for modeling some kind of induction generator configurations. To analyze more deeply the performance of the wind turbine system, both normal and fault conditions scenarios have been applied. Simulation results prove the excellent performance of the wind power unit under normal and fault conditions in the power distribution system.9. Fuzzy Multi-Objective Approach for the Improvement of Distribution Network Efficiency by Considering DG
Ramadoni Syahputra
April 2012 | Cited by 74
This paper presents a fuzzy multi-objective approach for achieving the minimum active power loss and the maximum voltage magnitude in order to improve the efficiency of radial distribution networks with distributed generations. Multi-objective function are considered for load balancing among the feeders, minimization of the real power loss, deviation of nodes voltage, and branch current constraint violation, while subject to a radial network structure in which all loads must be energized. Originality of the research is that the fuzzy-based multi-objective optimization in reconfiguration of distribution network including the distributed generation in order to improve the efficiency of the networks. The implementation of the fuzzy multi-objective for distribution reconfiguration on a 70 nodes distribution network with distributed generation is described. The original efficiency of the network is 95.142%. The simulation results show that efficiency of the network is increased to 96.942% by using fuzzy multiobjective method.10. Adaptive Fuzzy Filtering for Artifact Reduction in Compressed Images and Videos
P.Ramakrishna Rao, B.Addai, G.Ramakrishna and T.PanduRanga Vital
February 2011 | Cited by 72
In this paper, spatial neighboring pixels are used to deal with blocking and ringing artifacts while temporal neighboring pixels are utilized to remove mosquito and flickering artifacts. To avoid the blurring effect of linear filters, a fuzzy filter is implemented. Fuzzy filter is a specific case of bilateral filters [15], [16]. Fuzzy filters help denoising the artifacts while retaining the sharpness of real edges. In image and video compression, the artifacts such as blocking or ringing artifacts are spatially directional and flickering artifacts are temporally directional. For compressed video sequences, the motion compensated spatiotemporal filter (MCSTF) is applied to intraframe and interframe pixels to deal with both spatial and temporal artifacts. In this work, a novel fuzzy filter is proposed to adapt to the pixel�s activity and directions between the pixel of interest and its surrounding pixels.