Awais Adnan

Using the NS-2 Network Simulator for Evaluating Network on Chips (NoC)

Networks on chips (NoCs) have been introduced as a remedy for the growing problems of current interconnects in VLSI chips. Being a relatively new domain in research, simulation tools for NoCs are scarce. To fill the gap, we use network simulator NS-2 for simulating NoCs, especially at high level chip design. The huge library of network elements along with its flexibility to accommodate customized designs, NS-2 becomes a viable choice for NoCs. We have used NS-2 to simulate our prototype of a fault tolerant protocol for NoCs

Content Based Image Retrieval Using Geometrical-Shape of Objects in Image

Although some major advances have been made in text searching; only preliminary work has been done in image search. The field of Image search is rooted in Artificial intelligence, digital signal processing, statistics, natural language understanding, databases, psychology, computer vision, and pattern recognition. However none of these fields can solve the problem of image search alone but the solution lies at the crossroads of these parent fields. In our paper we are presenting a method of Contents Based Image Search where geometrical shapes of the objects in the image are considered as contents of image. Each object is separated from the image by segmentation. Then the geometrical shape of the object is estimated and compared with a predefine set of shapes of different categories. Number of objects in an image and geometrical shape of the objects are used as contents of the image which is used for retrieval and searching. Number on objects in the image is used for first level of indexing in search process. Currently we have restricted our objects to a fix number of basic geometrical shapes for simplicity but in futures these shapes can be extended and linked to the real world objects by using more complex equations and other features like color, texture and concept of correlation. Most of the existing image retrieval systems are based on text search using keywords that are annotated manually which involve the intellectual and emotional sides of the human. But in our proposed system this process is somewhat automatic.

A Survey of Routing Issues and Associated Protocols in Underwater Wireless Sensor Networks

Underwater wireless sensor networks are a newly emerging wireless technology in which small size sensors with limited energy and limited memory and bandwidth are deployed in deep sea water and various monitoring operations like tactical surveillance, environmental monitoring, and data collection are performed through these tiny sensors. Underwater wireless sensor networks are used for the exploration of underwater resources, oceanographic data collection, flood or disaster prevention, tactical surveillance systems, and unmanned underwater vehicles. Sensor nodes consist of a small memory, a central processing unit, and an antenna. Underwater networks are much different from terrestrial sensor networks as radio waves cannot be used in underwater wireless sensor networks. Acoustic channels are used for communication in deep sea water. Acoustic signals have many limitations, such as limited bandwidth, higher end-to-end delay, network path loss, higher propagation delay, and dynamic topology. Usually, these limitations result in higher energy consumption with a smaller number of packets delivered. The main aim nowadays is to operate sensor nodes having a smaller battery for a longer time in the network. This survey has discussed the state-of-the-art localization based and localization-free routing protocols. Routing associated issues in the area of underwater wireless sensor networks have also been discussed.

Inter-intra frame segmentation using colour and motion for region of interest coding of video

In this paper, we present a segmentation method that is based on combined colour with temporal features like motion vectors. In the past segmentation methods for region of interest (ROI) coding has only based segmentation on one feature such as motion, colour and luminance etc [1–2]. The segmentation system that we proposed is based on two features there by combining the strengths of each separate segmentation technique e.g. fidelity and consistency of region combined with moving regions. First of all we segment image (pixels level) inside frame based on colour and then in the second step we segments the images (block level) in a set of frames based on motion. This is initial work of our project where we want to compress video by removing perceptual redundancy based on human visual perceptual capabilities. Human perceive images in term of objects which can never be captured as a whole image or its global features. In order to identify the Region of Interest (ROI) from the frames (and sequence of frames), this efficient segmentation is very important. As a first step, for colour based image segmentation we use an efficient method where speed is our primary concern because we have to process multi frames per second and for motion based image segmentation we use block based motion estimation combined with a motion threshold. Quality of the motion segmentation will be considered in the second step where we use morphological operators to remove interior and exterior noise. Since segmentation is based on blocks, where we have quite less number of pixels than in the image, so speed in not such a big issue. For the third step we explore how to combine the motion and colour segmented images. Our first algorithm is based on combining the edges of the colour segmented image with the edges of the block based motion estimated image. We are working on other algorithms to try and obtain more concise and consistent results. This paper describes our first approach.

Comparison of Localization Free Routing Protocols in Underwater Wireless Sensor Networks

Underwater Wireless Sensor Network (UWSN) is newly developed branch of Wireless Sensor network (WSN). UWSN is used for exploration of underwater resources, oceanographic data collection, flood or disaster prevention, tactical surveillance system and unmanned underwater vehicles. UWSN uses sensors of small size with a limited energy, memory and allows limited range for communication. Due to multiple differences from terrestrial sensor network, radio waves cannot be used over here. Acoustic channel are used for communication in deep water, which has many limitations like low bandwidth, high end to end delay and path loss. With the above limitations while using acoustic waves, it is very important to develop energy efficient and reliable protocols. Energy efficient communication in underwater networks has become uttermost need of UWSN technology. The main aim nowadays is to operate sensor with smaller battery for a longer time. This paper will analyse various routing protocols in the area of UWSN through simulation. This paper will analyse Depth Based Routing (DBR), Energy Efficient Depth Based Routing (EEDBR) and Hop by Hop Dynamic Addressing Based (H2-DAB) protocol through simulation. This comparison is carried out on the basis of total consumed energy, end to end delay, path loss and data delivery ratio.

Implementation and analysis of clustering techniques applied on Pocket Switched Network

Clustering is an extraction of closely knitted groups from a set of nodes. Its benefits in social network range from applying marketing schemes on an appropriate interest group to social network analysis. It is also considered an important tool for efficient communication in an intermittent Pocket Switched Network (PSN). Contact probability between mobile devices in disrupted social networks greatly depends upon the mobility profile and level of relationships between the device holders. Unlike flat routing, scalable and efficient routing in these networks is highly dependent upon accurate derivation of social circles or clusters. This paper therefore evaluates existing clustering techniques for terrestrial social network with the end aim of minimizing communication overhead by identifying those message carriers that can bring message closer to destination node. In order to ensure intercluster routing, modification in existing schemes is proposed so as to detect bridge nodes between single hop destination clusters and to find path towards a disjoint destination cluster.

Foreground detection using background subtraction with histogram

In the background subtraction method one of the core issue is; how to setup the threshold value precisely at run time, which can ultimately overcome several bugs of this approach in the foreground detection. In the proposed algorithm the key feature of any foreground detection algorithm; motion is used however getting the threshold value from the original motion histogram is not possible, so for the said purpose smooth motion histogram is used in a systematic way to obtain the threshold value. In the proposed algorithm the main focus is to get a better estimation of threshold so that to get a dynamic value, from histogram at run time. If the proposed algorithm is used intelligently in terms of motion magnitude and motion direction it can distinguish accurately between background and foreground, camera motion along with camera motion and object motion.

Region-Based Security Architecture for DTN

Due to the disrupted nature of intermittently connected networks, traditional security infrastructure i.e., Public Key Infrastructure (PKI) suffers difficulty in security provision. Unlike PKI, Identity Based Cryptography (IBC) does not need end-to-end connectivity to trusted third party for certificate retrieval before message transmission. It enables a sender to create a valid public key of destination entity on fly and hence successfully works with the disrupted nature of delay tolerant network (DTN). An extension of IBC namely Hierarchical IBC (HIBC) efficiently provides secure communication in large sparsely populated and intermittently connected DTN regions with security servers working in hierarchy. In the paper we have proposed HIBC-based key management architecture for challenged DTN regions with Internet working as a backbone region. We have discussed mechanisms of secure communication between two end nodes that may either belong to same or different region(s) of similar or different security architectures.

A Real-Time Specific Weed Recognition System by Measuring Weeds Density through Mask Operation

The identification and classification of weeds are of major technical and economical importance in the agricultural industry. To automate these activities, like in shape, color and texture, weed control system is feasible. The goal of this paper is to build a real-time, machine vision weed control system that can detect weed locations. In order to accomplish this objective, a real-time robotic system is developed to identify and locate outdoor plants using machine vision technology and pattern recognition. The algorithm which is based on Measuring Weeds Density through Mask operation is developed to classify images into broad and narrow class for real-time selective herbicide application. The developed algorithm has been tested on weeds at various locations, which have shown that the algorithm to be very effectiveness in weed identification. Further the results show a very reliable performance on weeds under varying field conditions. The analysis of the results shows over 95 % classification accuracy over 170 sample images (broad and narrow) with 70 samples from each category of weeds.

A robust algorithm for detecting people in overhead views

In this research a human detection system is proposed in which people are viewed from an overhead camera with a wide angle lens. Due to perspective change a person can have different orientations and sizes at different positions in the scene relative to the optical centre. We exploit this property of the overhead camera and develop a novel algorithm which uses the variable size bounding boxes with different orientations, with respect to the radial distance of the center of the image. In these overhead view images we neither used any assumption about the pose or the visibility of a person nor imposed any restriction about the environment. When compare the results of proposed algorithm with a standard histogram of oriented gradient (HOG) algorithm, we achieve not only a huge gain in overall detection rate but also a significant improvement in reducing spurious detections per image. On average, 9 false detections occur per image. A new algorithm is proposed where transforming the image patch containing a person to remove positional dependency and then applying the HOG algorithm eliminates 98% of the spurious detections in noisy images from an industrial assembly line and detects people with a 95% efficiency.