Systems and Communications Commons^™

Robust Textural Features For Real Time Face Recognition, Chen Cui, Vijayan K. Asari, Andrew D. Braun

Vijayan K. Asari

Automatic face recognition in real life environment is challenged by various issues such as the object motion, lighting conditions, poses and expressions. In this paper, we present the development of a system based on a refined Enhanced Local Binary Pattern (ELBP) feature set and a Support Vector Machine (SVM) classifier to perform face recognition in a real life environment. Instead of counting the number of 1's in ELBP, we use the 8-bit code of the thresholded data as per the ELBP rule, and then binarize the image with a predefined threshold value, removing the small connections on the binarized image. …

Recent Progress In Wide-Area Surveillance: Protecting Our Pipeline Infrastructure, Vijayan K. Asari, Paheding Sidike, Chen Cui, Varun Santhaseelan

Vijayan K. Asari

The pipeline industry has millions of miles of pipes buried along the length and breadth of the country. Since none of the areas through which pipelines run are to be used for other activities, it needs to be monitored so as to know whether the right-of-way (RoW) of the pipeline is encroached upon at any point in time. Rapid advances made in the area of sensor technology have enabled the use of high end video acquisition systems to monitor the RoW of pipelines. The images captured by aerial data acquisition systems are affected by a host of factors that include …

Dense Point-Cloud Representation Of A Scene Using Monocular Vision, Yakov Diskin, Vijayan K. Asari

Vijayan K. Asari

We present a three-dimensional (3-D) reconstruction system designed to support various autonomous navigation applications. The system presented focuses on the 3-D reconstruction of a scene using only a single moving camera. Utilizing video frames captured at different points in time allows us to determine the depths of a scene. In this way, the system can be used to construct a point-cloud model of its unknown surroundings. We present the step-by-step methodology and analysis used in developing the 3-D reconstruction technique. We present a reconstruction framework that generates a primitive point cloud, which is computed based on feature matching and depth …

Gaussian Weighted Neighborhood Connectivity Of Nonlinear Line Attractor For Learning Complex Manifolds, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla

Vijayan K. Asari

The human brain has the capability to process high quantities of data quickly for detection and recognition tasks. These tasks are made simpler by the understanding of data, which intentionally removes redundancies found in higher dimensional data and maps the data onto a lower dimensional space. The brain then encodes manifolds created in these spaces, which reveal a specific state of the system. We propose to use a recurrent neural network, the nonlinear line attractor (NLA) network, for the encoding of these manifolds as specific states, which will draw untrained data towards one of the specific states that the NLA …

Histogram Of Oriented Phase And Gradient (Hopg) Descriptor For Improved Pedestrian Detection, Hussin Ragb, Vijayan K. Asari

Vijayan K. Asari

This paper presents a new pedestrian detection descriptor named Histogram of Oriented Phase and Gradient (HOPG) based on a combination of the Histogram of Oriented Phase (HOP) features and the Histogram of Oriented Gradient features (HOG). The proposed descriptor extracts the image information using both the gradient and phase congruency concepts. Although the HOG based method has been widely used in the human detection systems, it lacks to deal effectively with the images impacted by the illumination variations and cluttered background. By fusing HOP and HOG features, more structural information can be identified and localized in order to obtain more …

Multiclass Object Detection With Single Query In Hyperspectral Imagery Using Class-Associative Spectral Fringe-Adjusted Joint Transform Correlation, Paheding Sidike, Vijayan K. Asari, Mohammad S. Alam

Vijayan K. Asari

We present a deterministic object detection algorithm capable of detecting multiclass objects in hyperspectral imagery (HSI) without any training or preprocessing. The proposed method, which is named class-associative spectral fringe-adjusted joint transform correlation (CSFJTC), is based on joint transform correlation (JTC) between object and nonobject spectral signatures to search for a similar match, which only requires one query (training-free) from the object's spectral signature. Our method utilizes class-associative filtering, modified Fourier plane image subtraction, and fringe-adjusted JTC techniques in spectral correlation domain to perform the object detection task. The output of CSFJTC yields a pair of sharp correlation peaks for …

Histogram Of Oriented Phase (Hop): A New Descriptor Based On Phase Congruency, Hussin Ragb, Vijayan K. Asari

Vijayan K. Asari

In this paper we present a low level image descriptor called Histogram of Oriented Phase based on phase congruency concept and the Principal Component Analysis (PCA). Since the phase of the signal conveys more information regarding signal structure than the magnitude, the proposed descriptor can precisely identify and localize image features over the gradient based techniques, especially in the regions affected by illumination changes. The proposed features can be formed by extracting the phase congruency information for each pixel in the image with respect to its neighborhood. Histograms of the phase congruency values of the local regions in the image …

A Modular Approach For Key-Frame Selection In Wide Area Surveillance Video Analysis, Almabrok Essa, Paheding Sidike, Vijayan K. Asari

Vijayan K. Asari

This paper presents an efficient preprocessing algorithm for big data analysis. Our proposed key-frame selection method utilizes the statistical differences among subsequent frames to automatically select only the frames that contain the desired contextual information and discard the rest of the insignificant frames.

We anticipate that such key frame selection technique will have significant impact on wide area surveillance applications such as automatic object detection and recognition in aerial imagery. Three real-world datasets are used for evaluation and testing and the observed results are encouraging.

A Robust Fringe-Adjusted Joint Transform Correlator For Efficient Object Detection, Paheding Sidike, Vijayan K. Asari, Mohammad S. Alam

Vijayan K. Asari

The fringe-adjusted joint transform correlation (FJTC) technique has been widely used for real-time optical pattern recognition applications. However, the classical FJTC technique suffers from target distortions due to noise, scale, rotation and illumination variations of the targets in input scenes. Several improvements of the FJTC have been proposed in the literature to accommodate these problems. Some popular techniques such as synthetic discriminant function (SDF) based FJTC was designed to alleviate the problems of scale and rotation variations of the target, whereas wavelet based FJTC has been found to yield better performance for noisy targets in the input scenes. While these …

Efficient Macromodeling Techniques Of Distributed Networks Using Tabulated Data, Mohamed Sahouli

Electronic Thesis and Dissertation Repository

Efficient macromodeling techniques used to model multi-port distributed systems using tabulated data are presented. First a method to macromodel large multiport systems characterized by noisy frequency domain data is shown. The proposed method is based on the vector fitting algorithm and uses an instrumental variable approach and QR decomposition to formulate the least squares equations. The instrumental variable method minimizes the biasing effect of the least squares solution caused by the noise of the data samples while QR decomposition decouples the least squares equations of multiport systems described by common set of poles. It is illustrated, that the proposed approach …

Controlling And Processing Core For Wireless Implantable Telemetry System, Naeeme Modir

Electronic Thesis and Dissertation Repository

Wireless implantable telemetry systems are suitable choices for monitoring various physiological parameters such as blood pressure and volume. These systems typically compose of an internal device implanted into a living body captures the physiological data and sends them to an external base station located outside of the body for further processing. The internal device usually consists of a sensor interface to convert the collected data to electrical signals; a digital core to digitize the analog signals, process them and prepare them for transmission; an RF front-end to transmit the data outside the body and to receive the required commands from …

Examination Of The Nonlinear Dynamics And Possible Chaos Encryption In A Zeroth-Order Acousto-Optic Bragg Modulator With Feedback, Fares S. Almehmadi, Monish Ranjan Chatterjee

Electrical and Computer Engineering Faculty Publications

Zeroth-order chaos modulation in a Bragg cell is examined such that tracking problems due to spatial deflections of the first-order AO beam at the receiver may be avoided by switching to the undeviated zeroth-order beam.

Nonlinear Dynamics, Bifurcation Maps, Signal Encryption And Decryption Using Acousto-Optic Chaos Under A Variable Aperture Illumination, Monish Ranjan Chatterjee, Suman Chaparala

Electrical and Computer Engineering Faculty Publications

Bragg cell nonlinear dynamics and bifurcation properties under first-order feedback with variable aperture are examined. Chaotic encryption and recovery of low-bandwidth signals, and optimal performance are evaluated for fixed and variable apertures.

Design And Implementation Of Ccny Dc Microgrid Testbed, Mahmoud Saleh, Yusef Esa, Yassine Mhandi, Werner Brandauer, Ahmed Mohamed

Publications and Research

This paper presents the design, control, energy management, and implementation of the City College of New York (CCNY) direct current (DC) microgrid laboratory testbed. This facility was custom designed and implemented by researchers at CCNY with minimal off-the-shelf components to enable significant flexibility and reconfiguration capability. The microgrid consists of renewable energy resources, energy storage system and controllable loads, and can operate in either a grid-connected or an islanded mode. The design steps, requirements, and results of the developed testbed were discussed. Moreover, several operational scenarios were tested. The experimental results verify the applicability and flexibility of the developed microgrid …

Creation Of Carbon Nanotube Based Biosensors Through Dielectrophoretic Assembly, Nilan S. Mani, Steve Kim, Kaushik Annam, Danielle Bane, Guru Subramanyam

Guru Subramanyam

Due to their excellent electrical, optical, and mechanical properties, nanosized single wall carbon nanotubes (SWNTs) have attracted significant attention as a transducing element in nano-bio sensor research. Controlled assembly, device fabrication, and bio-functionalization of the SWNTs are crucial in creating the sensors. In this study, working biosensor platforms were created using dielectrophoretic assembly of single wall carbon nanotubes (SWNTs) as a bridge between two gold electrodes. SWNTs in a commercial SDS surfactant solution were dispensed in the gap between the two gold electrodes, followed by applying an ac voltage across the two electrodes. The dielectrophoresis aligns the CNTs and forms …

Dna Based Electrolyte/Separator For Lithium Battery Application, Jitendra Kumar, Fahima Ouchen-Bouchendouka, Devin A. Smarra, Guru Subramanyam, James Grote

Guru Subramanyam

In this study, we demonstrated the use of DNA-CTMA (DC) in combination with PolyVinylidene Fluoride (PVDF) as a host matrix or separator for Lithium based electrolyte to form solid polymer/gel like electrolyte for potential application in Li-ion batteries.

The addition of DC provided a better thermal stability of the composite electrolyte as shown by the thermos-gravimetric analysis (TGA). The AC conductivity measurements suggest that the addition of DC to the gel electrolyte had no effect on the overall ionic conductivity of the composite. The obtained films are flexible with high mechanical stretch-ability as compared to the gel type electrolytes only.

Segmentation Of Pulmonary Nodules In Computed Tomography Using A Regression Neural Network Approach And Its Application To The Lung Image Database Consortium And Image Database Resource Initiative Dataset, Temesguen Messay, Russell C. Hardie, Timothy R. Tuinstra

Russell C. Hardie

We present new pulmonary nodule segmentation algorithms for computed tomography (CT). These include a fully-automated (FA) system, a semi-automated (SA) system, and a hybrid system. Like most traditional systems, the new FA system requires only a single user-supplied cue point. On the other hand, the SA system represents a new algorithm class requiring 8 user-supplied control points. This does increase the burden on the user, but we show that the resulting system is highly robust and can handle a variety of challenging cases. The proposed hybrid system starts with the FA system.

If improved segmentation results are needed, the SA …

Scaled Synthetic Aperture Rader Development, Jason Garvey Schray

Master's Theses

Several previous Cal Poly thesis projects involve synthetic aperture radar (SAR), automatic target recognition (ATR), and tracking. SAR data was either accessed from a publicly available database or generated using complex computer modeling software. The motivation for this dual thesis project is to design and construct a scaled SAR system to support Cal Poly radar projects. Ideally this is a low-cost, high resolution SAR architecture that produces raw range Doppler data for any desired target area. To that end, a scaled SAR system was successfully designed, built, and tested. The current SAR system, however, does not perform azimuthal compression and …

Translation Of 'Profiles In Faith', Monish Ranjan Chatterjee

Monish R. Chatterjee

Sarat Chandra Chatterjee (1876-1938) may be considered one of the three most significant figures of the literary component of the Bengal Renaissance, the other two being Bankim Chandra Chatterjee (1838-1894) and Rabindranath Tagore (1861-1941). As much as Bankim Chandra is identified with the new age in the Bengali novel, and the development of serious vernacular journalism, and Rabindranath with modern/classical movements in Bengali poetry and music, along with novel ideas in methods of education and teaching, Sarat Chandra, as a novelist and storyteller, perfected the art of narration and critical analyses of a variety of contemporaneous social and political issues, …

Translation Of 'Seasons Of Life: A Panoramic Selection Of Songs By Rabindranath Tagore', Monish Ranjan Chatterjee

Monish R. Chatterjee

No abstract provided.