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Nagavelli, Sai Krishnanand Improve Nano-Cube Detection Performance Using A Method of Separate Training of Sample Subsets
Master of Computing and Information Systems, Youngstown State University, 2016, Department of Computer Science and Information Systems
The transmission electron microscopy (TEM) is an imaging technique whereby beams of electrons are driven through a thin specimen so that its structure on the nanoscale can be captured. Due to the unique capabilities of TEM, it has been applied to many fields such as the studies of biological tissues, virology, analyzing reactive chemical compounds, monitoring crystal growth and examining 3D printing quality, etc. As a result, a large quantity of TEM data has been produced that are far beyond human processing capabilities. This thesis applies an ensemble learning method based on the AdaBoost to automatically detect cubeshaped nanoparticles in a single TEM image. The specific aim is to improve the detection performance by training classifiers with different subsets of the original positive samples. The subsets are organized according to the degree of particle overlapping so that the classifier can pick up the Haar-like features that are more sensitive to overlapping. Promising results have been observed in the preliminary tests with a 7.89% increase of the overall detection rate.

Committee:

Yong Zhang, PhD (Advisor); Feng George Yu, PhD (Advisor); John Sullins, PhD (Committee Member)

Subjects:

Computer Science

Keywords:

Integral image; Cascade classifier; Adaboost algorithm; Transmission electron microscopy; Rapid HAAR feature; OpenCV; Image detection

Van Hook, Richard L.A Comparison of Monocular Camera Calibration Techniques
Master of Science in Computer Engineering (MSCE), Wright State University, 2014, Computer Engineering
Extensive use of visible electro-optical (visEO) cameras for machine vision techniques shows that most camera systems produce distorted imagery. This thesis investigates and compares several of the most common techniques for correcting the distortions based on a pinhole camera model. The methods being examined include a common chessboard pattern based on (Sturm 1999), (Z. Zhang 1999), and (Z. Zhang 2000), as well as two "circleboard" patterns based on (Heikkila 2000). Additionally, camera models from the visual structure from motion (VSFM) software (Wu n.d.) are used. By comparing reprojection error from similar data sets, it can be shown that the asymmetric circleboard performs the best. Finally, a software tool is presented to assist researchers with the procedure for calibration using a well-known fiducial.

Committee:

Kuldip Rattan, Ph.D. (Advisor); Juan Vasquez, Ph.D. (Committee Member); Thomas Wischgoll, Ph.D. (Committee Member)

Subjects:

Computer Engineering; Computer Science; Optics; Scientific Imaging

Keywords:

Calibration; Reprojection Error; Visual Structure from Motion; OpenCV; calibration patterns

Subramanian, Shreyas VathulApplication of Auto-tracking to the Study of Insect Body Kinematics in Maneuver Flight
Master of Science in Engineering (MSEgr), Wright State University, 2012, Mechanical Engineering
There is a need to explain the complex phenomena that underlies the seemingly effortless flight modes of the dragonfly (Infra -order Anisoptera). However, measuring the body kinematics during flight is labor intensive. Thus a robust system was developed that automatically tracks and quantifies the body kinematics of a dragonfly during voluntary and escape take-offs, as well as maneuvers. Ultimately, the tool, which was developed using a custom code in C++ using the open source library OpenCV (Open Computer Vision), would be used to analyze bulk samples of high speed videos providing raw images at the rate of approximately 1000 frames per second from pair-wise orthogonal positions in space. As a result, there would be a considerably large database of information which may then be used to formulate, generalize and classify standard flight strategies used. Perceptibly, there is also a need to validate the outputs of this tool by comparing it to the outputs of a manual reconstruction.

Committee:

Haibo Dong, PhD (Advisor); Nasser Kashou, PhD (Committee Member); Hui Wan, PhD (Committee Member)

Subjects:

Aerospace Engineering

Keywords:

Insect Flight; Auto-tracking; Image Processing; OpenCV

Gao, WeihaoFACE RECOGNITION APPLICATION BASED ON EMBEDDED SYSTEM
Master of Engineering, Case Western Reserve University, 2013, EECS - Computer Engineering
The purpose of this application is to develop an embedded system application which is able to collect face image and recognize the face by comparing with the database inside the system. Face recognition as a type of biometric methods has the features of non-contact, safety and convenience. It is widely used in human-computer interaction, transaction authentication, security and other fields. Recent years, with the development of mobile internet and embedded computer, it becomes possible to run face recognition on embedded system. This type of application has huge potential in remote payment and personal information security. This application is running on Android operating system which is an operating system based on the Linux kernel, and designed primarily for touchscreen mobile devices such as smartphones and tablet computers. The procedure of face recognition includes face detection, face normalization and recognition. This paper studies these key issues and successfully developed an application with nice recognition rate. The main contents and results are as follows: 1) Discusses the face detection method. It used Adaboost algorithm and Haar features to detect human faces. 2) Studies image pre-processing methods. Standardize the images so as to minimize the storage space and speed up the computation speed. 3) Summarize a variety of face recognition algorithms especially principle component analysis which is used in this application. Discuss the theoretical foundation of PCA algorithm. 4) Fulfilled all the features from face detection to recognition in Android platform. Using ORL face image database for testing and got a correct identification rate of over 85%. Fully verify the effectiveness of the program. Discuss the results and identification strategies.

Committee:

Christos Papachristou (Advisor)

Subjects:

Computer Engineering; Computer Science

Keywords:

Android; OpenCV; Adaboost; Face recognition; PCA

Govindaraajan, SrikkanthDesign and Implementation of a Vascular Pattern Recognition System
MS, University of Cincinnati, 2014, Engineering and Applied Science: Electrical Engineering
Biometric technology is playing a vital role in the present day due to the rapid development of secure systems and home automation that have made our lives easier. But the question arises as to how far these systems are secure. With advances in hacking, the traditional username and password security protocol is not optimal for all security based systems. Though fingerprint identification systems provided a path-breaking solution, there are many methods to forge fingerprints. While other technologies like voice recognition, iris recognition, etc., co-exist, the security and safety of these technologies are also open to question. The major objective of this thesis is to provide enhanced security through a biometrics based embedded system using the technique of Vascular Pattern Recognition or Vein Pattern Recognition (VPR). Another objective is to enhance the vascular pattern image through various image processing techniques. Another target is to reduce the Comparison for Result (CFR) time by a significant factor. Finally, the aim is to implement this VPR based embedded system in a real time software environment. For the system we implemented, our experiments achieved a false accept rate of 0% and a false reject rate of 6.34%. Furthermore, it has been demonstrated in our research that the Speeded Up Robust Features (SURF) algorithm is faster than its predecessor algorithm Scale Invariant Feature Transform (SIFT). The principal conclusion of the thesis is that a safe and secure system can be developed on a small scale with precise results. Given the resources, this system could be extended to a larger scale and customized for a wide range of applications.

Committee:

Carla Purdy, Ph.D. (Committee Chair); Wen Ben Jone, Ph.D. (Committee Member); George Purdy, Ph.D. (Committee Member)

Subjects:

Computer Engineering

Keywords:

Vascular Pattern Recognition;Vein Pattern Recognition;Image processing techniques;SURF algorithm;OpenCV

Xiang, ChangshengA New Way for Mapping Texture onto 3D Face Model
Master of Science (M.S.), University of Dayton, 2015, Electrical Engineering
Adding texture to an object is extremely important for the enhancement of the 3D model's visual realism. This thesis presents a new method for mapping texture onto a 3D face model. The complete architecture of the new method is described. In this thesis, there are two main parts, one is 3D mesh modifying and the other is image processing. In 3D mesh modifying part, we use one face obj file as the 3D mesh file. Based on the coordinates and indices of that file, a 3D face wireframe can be displayed on screen by using OpenGL API. The most common method for mapping texture onto 3D mesh is to do mesh parametrization. To achieve this goal, a perspective-projection method is used to map 3D mesh to a 2D plane. To improve the degree of the accuracy, we separates the 3D mesh into three pieces based on three different view positions from left to right. In image processing part, we extracted the face information from the green back- ground images by using image segmentation. Because of the three face images from different view positions, so they have different light illumination. In this thesis, a button controller was made to control the light illumination of three parts separately. The image blending method was used to reduce the texture seam between two different parts of the mesh. The proposed method in this thesis is new way to add detail to a 3D model. It provides a valid texture mapping, also satisfies the man-machine interaction exactly. Even if the images are taken under the different illumination, users can use keyboard to change its illumination for color matching. This new way provides a new method to parametrize and modify the mesh so as to be used for texture mapping.

Committee:

John S. Loomis, Dr. (Advisor)

Subjects:

Computer Engineering; Computer Science; Electrical Engineering

Keywords:

texture mapping; 3D face model; mesh parametrization; image processing; OpenGL; OpenCV

hart, charlesA Low-cost Omni-directional Visual Bearing Only Localization System
Master of Sciences, Case Western Reserve University, 2014, EECS - Computer and Information Sciences
RAMBLER Robot is designed to enable research on biologically inspired behavioral robot control algorithms. RAMBLER Robot tests the feasibility of autonomously localizing without typical sensors like wheel odometers or GPS. The primary objective is to independently, accurately, and robustly recover the path of a moving robotic system with only the lowest-cost sensors available off-the-shelf. Methods new and old are reviewed and tested on the real RAMBLER Robot hardware. The hardware and software necessary to use omni-directional camera measurements to decrease uncertainty regarding the position and heading of a small robot system are presented in detail. The RAMBLER Robot is shown to successfully localize within a small arena using three passive indistinguishable landmarks.

Committee:

Roger Quinn (Committee Chair); Francis Merat (Committee Member); Gregory Lee (Committee Member)

Subjects:

Computer Science; Robotics

Keywords:

omnicam; camera; omnidirectional; panoramic; catadioptric; spherical reflector; triangulation; power center; localization; particle filter; computer vision; raspberry pi; zumo; robot; robotics; low-cost; inexpensive; python; matlab; opencv;