Spiral Bit-string Representation of Color
for Image Retrieval

Abdelhamid Abdesselam1, Hui Hui Wang2, and Narayanan Kulathuramaiyer2
1Department of Computer Science, Sultan Qaboos University, Oman
2Faculty of Computer Science and Information Technology, UNIMAS, Malaysia

Abstract: This paper describes a color-based image retrieval technique that uses a new representation for the color content of an image. The new representation, called Spiral Bit-string Representation, is an extension of the traditional bitmap signature representation, where the image description is performed in a spiral manner, starting from the centre of the image and moving clockwise towards the border. The major advantages of this representation are its simplicity, its suitability for retrieval of rotated and scaled images as well as for sub-image querying.

Keywords: Color Image Retrieval, bit-string representation, rotation-invariant, scale-invariant.

Chaos-Based Key Stream Generator
Based on Multiple Maps Combinations and its Application to Images Encryption

Abstract: : In recent years, growing number of cryptosystems based on chaos have been proposed. However, most of them encounter some problems such as: low level of security and small key space. The key stream generator is the key design issue of an encryption system. It directly determines security and efficiency, but most of the proposed key streams are binary valued, and suffer from short period and limited key space. In this paper, we propose an n-ary key stream generator, based on hierarchical combination of three chaotic maps. We demonstrate that the produced key streams have good statistical properties, such as uniform distribution, δ-like auto-correlation function, near-zero cross-correlation and very height sensitivity to initial conditions, under precision restricted condition. An image cryptosystem is constructed using the proposed approach and proven to be enough secure to resist various attacks. Complexity is analysed and an effective acceleration of chaos-based image cryptosystems is shown to be achievable.

Keywords: Chaotic maps, images cryptography, key stream generation, security.

Received December 1, 2008; accepted January 27, 2009

Mining Multiple Large Data Sources

Keywords: Multi-database mining, pipelined feedback technique, synthesis of patterns.

Received December 21, 2008; accepted February 8, 2009

Development of Neural Networks for Noise Reduction

Uplink Downlink Limited Round Robin
Scheduling Algorithms

Complex Gain Predistortion in WCDMA Power Amplifiers with Memory Effects

Mediation Queries Adaptation After the
Removal of a Data Source

Synthesis of Multibeam Antennas Arrays with a Modified Particle Swarm Optimization Algorithm

Improving the Effectiveness of the
Color Coherence Vector

Prolonging Network Lifetime and Data Accumulation in Heterogeneous Sensor Networks

Dilip Kumar1, Trilok Chand Aseri2, and Ram Bahadur Patel3
1Centre for Development of Advanced Computing, Ministry of Communication & IT, India
PEC University of Technology, India
3Department of Computer Science and Engineering, Maharishi Markandeshwar University, India

Abstract: Research on Wireless Sensor Networks has often assumed homogeneous nodes. In reality, homogeneous nodes have different capabilities like different levels of initial energy and drain rate. This leads to the research on heterogeneous networks where two or more types of nodes are considered within the network and the more powerful sensor nodes act as cluster heads. In this paper, we have analyzed a heterogeneous network with three types of nodes having different initial energy levels.  A single hop clustering topology has been assumed and analyzed the network performance in terms of lifetime. Simulation results show that the network lifetime is much better in proposed protocol than the existing protocols.

Keywords: Wireless sensor networks, heterogeneous, lifetime, clustering.

Innovative Algorithms for the Header
Processing Transition from IPv4 to IPv6
and Vice Versa

Keywords: IPv4/IPv6 transition, IPv4/IPv6 header processing, IP tunneling, IP encapsulation, address mapping, dual stack.

Received November 9, 2008; accepted April 14, 2009

Improving Fuzzy Algorithms for Automatic Magnetic Resonance Image Segmentation

Abstract: In this paper, we present reliable algorithms for fuzzy k-means and C-means that could improve MRI segmentation. Since the k-means or FCM method aims to minimize the sum of squared distances from all points to their cluster centers, this should result in compact clusters. Therefore the distance of the points from their cluster centre is used to determine whether the clusters are compact. For this purpose, we use the intra-cluster distance measure, which is simply the median distance between a point and its cluster centre. The intra-cluster is used to give us the ideal number of clusters automatically; i.e a centre of the first cluster is used to estimate the second cluster, while an intra-cluster of the second cluster is obtained. Similar, the third cluster is estimated based on the second cluster information (centre and intra cluster), so on, and only stop when the intra-cluster is smaller than a prescribe value. The proposed algorithms are evaluated and compared with established fuzzy k-means and C-means methods by applying them on simulated volumetric MRI and real MRI data to prove their efficiency. These evaluations, which are not easy to specify in the absence of any prior knowledge about resulted clusters, for real MRI dataset are judged visually by specialists since a real MRI dataset cannot give us a quantitative measure about how much they are successful.

Keywords:Machine learning, medical imaging, fuzzy clustering, image segmentation, clustering validation.

Received April 12,  2008; accepted February 8, 2009

3D Model Retrieval Based on 3D
Discrete Cosine Transform

Elmustapha Ait Lmaati, Ahmed El Oirrak, Mohamaed Najib Kaddioui, Abdellah Ait Ouahman, and Mohammed Sadgal  
Department of Computer Science, Cadi Ayyad University, Morocco

Abstract: The content-based retrieval systems for 3D models on the Web become necessary since digital databases of 3D objects are growing. In this paper, we propose a new method to describe 3D models. This method is based on 3D discrete cosine transform  which is applied for the voxelized 3D model. The discrete cosine transform is widely used for 2D image compression and it shows its performance for the JPEG compression algorithm. The proposed descriptor is implemented in our 3D search engine, tested using the princeton shape benchmark database, tested for noise and decimation; and compared to other 3D descriptors known in the literature.

Keywords: Search engine, 3D models, retrieval systems, 3D discrete cosine transform.

Realization of a Novel Fault Tolerant Reversible Full Adder Circuit in Nanotechnology

Keywords: Reversible logic, reversible gate, parity preserving reversible gates, conservative reversible gate, and reversible full adder circuit.

Received September 10, 2008; accepted May 17, 2009

Multiple Warehouses Scheduling Using
Steady State Genetic Algorithms

Abstract: Warehouses scheduling is the problem of sequencing requests of products to fulfill several customers’ orders so as to minimize the average time and shipping costs. In this paper, a solution to the problem of multiple warehouses scheduling using the steady state genetic algorithm is presented. A mathematical model that organizes the relationships between customers and warehouses is also presented in this paper. Two scenarios of storage capacities (constants and varying capacities) and two strategies of search points (ideal point and random points) are compared. An analysis of the results indicates that  multiple warehouses scheduling using the GENITOR approach with different warehouses capacities have better outcome than the usage of the traditional genetic algorithms).

Keywords: Multiple warehouse scheduling, genitor, ideal point search strategy, random point search strategy.

Received October 27, 2008; accepted May 17, 2009