|Title: AES Based Security Architecture Of WIMAX Using OMNET++|
|Author(s): Romana shahzadi, Asim Shahzad|
|Pages: 1-4||Paper ID: 90610-3939-IJET-IJENS||Published: December, 2009|
Abstract: Although WiMAX is considered to be the last mile protocol but its security still remains a question because it neither encrypts the MAC (Media access control) headers nor the media MAC management messages. Therefore, an attacker can easily launch passive attacks to monitor WiMAX traffic and can retrieve valuable information from unencrypted MAC management messages. This research paper focuses on the analysis of security threats and their mitigation at MAC Layer of WiMAX. PKM (Privacy and Key management) protocol is used in this regard to gain authorization and traffic keying material between the Base Station to Subscriber Station, and to maintain periodic reauthorization and key refresh. The 128 bit key based AES (Advance Encryption Standard) encryption is also implemented. The target is to encrypt communication between WIMAX based BS (Base station) and MS/SS(Mobile station/subscriber station) using AES where encryption is applied on all the packets exchanged. All the simulations are made in OMNET++ and visual C++ language to visualize encrypted packet transmission between BS and SS.
|Keywords: Privacy Key Management(PKM), Advance Encryption Standard(AES), Subscriber Station (SS), Base Station (BS), Authorization Key(AK).|
|Full Text (.pdf) | 270 KB|
|Title: Image Retrieval Using Cubic Splies Neural Networks|
|Author(s): Samy Sadek, Ayoub Al-Hamadi, Bernd Michaelis, Usama Sayed|
|Pages: 5-9||Paper ID: 92910-1919-IJET-IJENS||Published: December, 2009|
Abstract: Most of the approaches of Content-Based Image Retrieval (CBIR) presume a linear relationship between different image features, and the efficiency of such systems was limited due to the difficulty in representing high-level concepts using low-level features. In this paper, a new architecture for a CBIR system is proposed; the Splines Neural Network-based Image Retrieval (SNNIR) system. SNNIR makes use of a rapid and precise network model that employs a cubic-splines activation function. By using the cubic-splines network, the proposed system could determine nonlinear relationship between images features so that more accurate similarity comparison between images can be supported. Experimental results show that the proposed system achieves high accuracy and effectiveness in terms of precision and recall compared to other CBIR systems.
|Keywords: Splines neural network, Feature extraction, Content-based image retrieval.|
|Full Text (.pdf) | 499 KB|
|Title: Development Of Handwritten Myanmar Alphabet Recognition|
|Author(s): Yu Yu Than, Darli Myint Aung, Aye Mon Yi, Kay Thi Win|
|Pages: 10-13||Paper ID: 95210-8383-IJET-IJENS||Published: December, 2009|
Abstract: The reading of characters by computer is known as Optical Character Recognition (OCR). OCR is one of the popular applications of image processing systems. OCR has many different practical applications. This paper is to develop the handwritten Myanmar alphabet recognition (HMAR) system which is able to evaluate the performance of Handwritten Optical Character Recognition (HW-OCR). This HMAR system is able to recognize handwritten character of several different writing styles. This paper presents the feature extraction method for the handwritten Myanmar alphabet based on the zoning method. The development of rule-based recognition system for Myanmar alphabet is supported as a result to obtain better recognition accuracy rate.
|Keywords: Myanmar Alphabet, OCR|
|Full Text (.pdf) | 154 KB|
|Title: An Efficient Rate Allocation Scheme with Selective Weighted Function for Optimum Peak-to-Average Power Ratio for Transmission of Image Streams Over OFDM Channels|
|Author(s): Usama S. Mohammed, H. A. Hamada|
|Pages: 14-26||Paper ID: 95610-7474-IJET-IJENS||Published: December, 2009|
Abstract: This paper proposes new scheme for efficient rate allocation in conjunction with reducing peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing (OFDM) system. Modification of the set partitioning in hierarchical trees (SPIHT) image coder is proposed to generate four different groups of bit-stream relative to its significances. The significant bits, the sign bits, the set bits and the refinement bits are transmitted in four different groups. The proposed method for reducing the PAPR utilizes twice the unequal error protection (UEP) using the Read-Solomon codes (RS) in conjunction with bit-rate allocation. The output bit-stream from the source code (SPIHT) will be started by the most significant types of bits (first group of bits). The optimal unequal error protection (UEP) of the four groups is proposed. As a result, the proposed structure gives a significant improvement in bit error rate (BER) performance. Performed computer simulations have shown that the proposed scheme outperform the performance of most of the recent PAPR reduction techniques in most cases. Moreover, the simulation results indicate that the proposed scheme provides significantly better PSNR performance in comparison to well-known robust coding schemes.
|Keywords: SPIHT coding, unequal error protection (UEP), rate allocation, RS codes, OFDM, PAPR.|
|Full Text (.pdf) | 1,014 KB|
|Title: Blind Separation of Nonlinear Mixing Signals Using Kernel with Slow Feature Analysis|
|Author(s): Usama S. Mohmmed, Hany Saber|
|Pages: 27-32||Paper ID: 96310-7676-IJET-IJENS||Published: December, 2009|
Abstract: This paper describes a hybrid blind source separation approach (HBSSA) for nonlinear mixing model (NL-BSS). The proposed hybrid scheme combines simply the kernel-feature spaces separation technique (KTDSEP) and the principle of the slow feature analysis (SFA). The nonlinear mixed data is mapped to high dimensional feature space using kernel-based method. Then, the linear blind source separation (BSS) based on the slow feature analysis (SFA) is used to extract the most slowness vectors among the independent data vectors. The proposed scheme is based on the following four key features: 1) estimating an orthonormal bases, 2) mapping the data into the subspace using this orthonormal bases, 3) applying linear BSS on the mapping data to make the data vectors in the feature spaces are independent, 4) Applying the principle of slow feature analysis on the mapping data to select the desired signals. The SFA provides the dimension reduction according to the most independent and slowing variable signals. Moreover, the orthonormal bases estimation in the wavelet domain is introduced in this work to reduce the complexity of the KTDSEP algorithm. The motivation of using the wavelet transform, in estimating the orthonormal bases, is based on the fact that the low frequency band in the wavelet domain contains the significant power of the signal. The advantages of the proposed method are the fast estimation of the orthonormal bases and the dimension reduction of the estimating data vectors. Performed computer simulations have shown the effectiveness of the idea, even in presence of strong nonlinearities and synthetic mixture of real world data. Our extensive experiments have confirmed that the proposed procedure provides promising results.
|Keywords: Nonlinear blind source separation, slow feature analysis, independent slow feature analysis, slow feature analysis, kernel base algorithm, and kernel trick|
|Full Text (.pdf) | 1,105 KB|
|Title: Enhancement of Bone Fracture Image Using Filtering Techniques|
|Author(s): Muhammad Luqman Bin Muhd Zain, Irraivan Elamvazuthi, Mumtaj Begam|
|Pages: 33-37||Paper ID: 96510-2929-IJET-IJENS||Published: December, 2009|
Abstract: Ultrasound imaging has been introduced to provide a non-invasive and nondestructive technique either in industrial or medical field. In the medical field, ultrasound is broadly used for fetal and cancer disease detection and less for long bone fracture detection. This is mainly due to the formation of speckles in the ultrasound images which make the images unclear for fast interpretation. Therefore, a study was carried out to enhance the ultrasound images of long bone fracture. This involved image contrast enhancement and speckle reduction using filtering techniques such as Wiener, Average and Median Filters. This paper discusses the level of improvement obtained through these three filtering techniques. It was found through visual inspection and histogram analysis that amongst the three techniques, the Wiener Filtering is a better technique in reducing the speckle without fully eliminating the image edges.
|Keywords: Ultrasound imaging, wiener filter, average filter, median filter, histogram equalization, contrast enhancement.|
|Full Text (.pdf) | 503 KB|
|Title: Video Multicasting in Campus Networks|
|Author(s): Mehmet Ordukaya, Hakki Alparslan Ilgin|
|Pages: 38-43||Paper ID: 97910-2727-IJET-IJENS||Published: December, 2009|
Abstract: We consider distribution of video over IP multicast in campus network of universities or large companies under real-time delay conditions. In the study, an experimental test model is designed which consists of hardware and software applications and in which real-time delays are experienced and the networks having different physical conditions within the campus can receive data in different qualities. In addition to channel heterogeneity, available CPU power of receivers affects decoding of incoming signal. In this paper, we propose a network structure for a video multicast system and show experimental results obtained in the implementation.
|Keywords: Remote Networks, Serial Communication Technologies, Video Coding, Video Multicast, Video multicast in large LANs.|
|Full Text (.pdf) | 385 KB|
|Title: A New Video Coding Approach Based on Object-Extraction|
|Author(s): Usama S. Mohammed, Walaa M. Abd-Elhafiez|
|Pages: 44-52||Paper ID: 98410-0303-IJET-IJENS||Published: December, 2009|
Abstract: This paper describes efficient object-based video coding schemes suitable for content-based multimedia streaming systems. Anew two video coding approaches are presented to study the effect of the object based motion estimation in video coding and the effect of the object based video coding on the compression quality, respectively. The first approach is based on a new motion estimation technique; based on arbitrary shaped-regions. The second approach is based on the video object extraction and a new motion estimation technique based on arbitrary shaped-regions. The proposed methods are applied on videos containing a variety of scenarios such as multiple objects undergoing occlusion, splitting, merging, entering and exiting, as well as a changing background. The simulation results are introduced in a comparison form with some of recent video coding method. For all the videos, the proposed approach displays higher Peak Signal to Noise Ratio (PSNR) compared to other methods, and provides comparable or better compression than some of recent video coding techniques.
|Keywords: Video coding; image segmentation; object extraction; MPEG-4; video object planes (VOPs); motion vectors estimation.|
|Full Text (.pdf) | 708 KB|