Kamesh Namuduri

Automated detection and classification of vascular abnormalities in diabetic retinopathy

Diabetic retinopathy is a progressive ocular disease. The disease may advance from mild to severe non-proliferative diabetic retinopathy. This paper proposes a method for automated detection and classification of vascular abnormalities in diabetic retinopathy. The vascular abnormalities are detected using scale and orientation selective Gabor filter banks. The proposed method classifies the retinal image as mild or severe case based on the outputs obtained from Gabor filters.

HORNS: A homomorphic encryption scheme for Cloud Computing using Residue Number System

In this paper, we propose a homomorphic encryption scheme using Residue Number System (RNS). In this scheme, a secret is split into multiple shares on which computations can be performed independently. Security is enhanced by not allowing the independent clouds to collude. Efficiency is achieved through the use of smaller shares.

Compact combination of MPEG-7 color and texture descriptors for image retrieval

Multimedia databases are meaningfully indexed and retrieved with content based image retrieval (CBIR) systems. MPEG-7 standard describes visual descriptors and performance metrics for CBIR systems. Amongst all image features, color and texture are more visually expressive and hence are attractive for image retrieval descriptors enhances image retrieval and efficiency of a multimedia database. Further, combination of features makes image retrieval more relevant and robust. This paper proposes efficient methods for compactly representing color and texture features and combining them for image retrieval. The proposed methods use MPEG-7 visual descriptors namely, scalable color descriptor (SCD) for color and, homogeneous texture descriptor (HTD) for texture representation respectively. This paper investigates how compactly a descriptor could be defined and yet be used as a metric for image retrieval. If the descriptor is compact and yet performs meaningful image retrieval, then it is computationally efficient. Image classification, clustering and hierarchical modeling of image databases will benefit with such a representation. The performance of retrieval based on compact descriptors obtained by proposed techniques is analyzed with MPEG-7 metrics.

A Survey and Analysis of Mobility Models for Airborne Networks

Mobility models serve as the foundation for evaluating and designing airborne networks (ANs). Due to the significant impact of mobility models on the networking performance, the mobility models must realistically capture the attributes of ANs. In this paper, we present a comprehensive survey and comparative analysis of mobility models that are either adapted to or developed for AN evaluation purposes. We evaluate these mobility models based on the following metrics: adaptability, networking performance, and ability to realistically capture the mobility attributes of ANs (including high mobility, mechanical and aerodynamic constraint, and safety requirements). To provide a deeper understanding and facilitate the selection and configuration of these mobility models, we also evaluate them based on randomness levels and associated applications.

A smooth-turn mobility model for airborne networks

The design of effective routing protocols in airborne networks (ANs) relies on suitable mobility models that capture the movement patterns of airborne vehicles. As airborne vehicles cannot make sharp turns as easily as ground vehicles do, the widely used ground-based mobile ad hoc network (MANET) mobility models are not appropriate to use as the analytical frameworks for airborne networking. In this paper, we introduce a novel mobility model, which is called the smooth-turn (ST) mobility model, that captures the correlation of acceleration of airborne vehicles across temporal and spatial coordinates. The proposed model is realistic in capturing the tendency of airborne vehicles toward making straight trajectories and STs with large radii, yet is tractable enough for analysis and design. We first describe the mathematics of this model and then prove that the stationary node distribution is uniform. Furthermore, we introduce a metric to quantify the degree of model randomness, and using this, we compare and classify several mobility models in the literature. We conclude this paper with several possible variations to the basic ST mobility model.

A Smooth-Turn Mobility Model for Airborne Networks

The design of effective routing protocols in airborne networks (ANs) relies on suitable mobility models that capture the movement patterns of airborne vehicles. As airborne vehicles cannot make sharp turns as easily as ground vehicles do, the widely used ground-based mobile ad hoc network (MANET) mobility models are not appropriate to use as the analytical frameworks for airborne networking. In this paper, we introduce a novel mobility model, which is called the smooth-turn (ST) mobility model, that captures the correlation of acceleration of airborne vehicles across temporal and spatial coordinates. The proposed model is realistic in capturing the tendency of airborne vehicles toward making straight trajectories and STs with large radii, yet is tractable enough for analysis and design. We first describe the mathematics of this model and then prove that the stationary node distribution is uniform. Furthermore, we introduce a metric to quantify the degree of model randomness, and using this, we compare and classify several mobility models in the literature. We conclude this paper with several possible variations to the basic ST mobility model.

Airborne network: a cyber-physical system perspective

An airborne network is a cyberphysical system (CPS) in which there is an intense interaction between the physical and cyber components. While computation, communication and networking elements form the cyber components of the system, fight-paths, manoeuvre geometries, and multimode resources including ground-based nodes and control stations form the physical components of the CPS. The synergy between the cyber and physical components, if explored and exploited, will signicantly enhance the safety and security capabilities of Next Generation (NextGen) air transportation systems. In this paper, we characterize airborne networks based on their mobility patterns, path predictability, and model complexity. We discuss mobility models suitable for airborne networks, analytical models for estimating the link/path duration in airborne networks, and strategies for information assurance in airborne networks.

OCTOPUS: An On-Demand Communication Topology Updating Strategy for Mobile Sensor Networks

Mobile sensor networks are characterized by dynamic changes in communication links and network topology caused mainly due to node mobility. In such networks, it is a challenge to build a communication system that lasts longer and requires less reconfiguration and less communication overhead. In this paper, we propose an on-demand topology reconfiguration approach for mobile sensor networks aimed at enhancing the connectivity and performance. The proposed strategy groups nodes, elects cluster-heads, and, finally, selects gateways for inter-cluster communication. Neural networks are used to form clusters. Cluster-heads are elected based on the concept of minimum dominant set and the gateways are selected based on a willingness function. We demonstrate through simulations that the proposed strategy results in a well connected network.

Automatic extraction of highlights from a cricket video using MPEG-7 descriptors

Sports videos appeal to a vast majority of people. Hence, video streaming of sports videos presents a profitable business opportunity. As a result, there is an astronomical increase in the amount of sports content available on the internet. Businesses and users face a new problem of perusing such large amounts of multimedia content quickly for the required information. One technique that can enable quick overview of multimedia content is video summarization. In this paper, an approach to summarize a cricket game video by using highlights extraction process is presented. The video is first segmented into shots. Key frames are extracted from each shot and low level features are extracted from the key frames. Feature are used to extract views or states. The states and their transitions in the cricket game are represented by a Hidden Markov Model, based on which the game highlights are extracted. The performance of the proposed summarization scheme is evaluated for accuracy.

Object tracking in video using particle filtering

Object tracking in video is an important problem which has many applications, such as video surveillance, target tracking using video sensors, etc. The paper presents an approach to object tracking in a video sequence using particle filtering. The motion edge is modelled using a six parameter model. Spatio-temporal filtering techniques are used to determine the velocity of the moving edge. Particle filtering is used to propagate the multi dimensional posterior density over time. Experimental results are presented to show the effectiveness of the proposed method.