Electrical and Computer Engineering Commons^™

Investigation Of Green Strawberry Detection Using R-Cnn With Various Architectures, Daniel W. Rivers

Master's Theses

Traditional image processing solutions have been applied in the past to detect and count strawberries. These methods typically involve feature extraction followed by object detection using one or more features. Some object detection problems can be ambiguous as to what features are relevant and the solutions to many problems are only fully realized when the modern approach has been applied and tested, such as deep learning.

In this work, we investigate the use of R-CNN for green strawberry detection. The object detection involves finding regions of interest (ROIs) in field images using the selective segmentation algorithm and inputting these regions …

Synthetic Aperture Optical Imaging Interferometric Microscopy With Improved Image Quality, Preyom K. Dey

Electrical and Computer Engineering ETDs

The resolution limit of optical microscopy can be extended by using Imaging Interferometric Microscopy (IIM), which uses a low numerical aperture (NA) objective lens to achieve resolution equivalent to that of a high-NA objective lens with multiple sub-images. Along with the resolution enhancement challenge, IIM often suffers from poor image quality. In this dissertation, several image quality improvement methods are proposed and verified with simulation and experimental results. Next, techniques to extend the resolution limit of IIM to ≤ 100nm using a low-NA objective lens are demonstrated. An experimental technique of using a grating coupler on …

Pneumonia Radiograph Diagnosis Utilizing Deep Learning Network, Wesley O'Quinn

Honors College Theses

Pneumonia is a life-threatening respiratory disease caused by bacterial infection. The goal of this study is to develop an algorithm using Convolutional Neural Networks (CNNs) to detect visual signals for pneumonia in medical images and make a diagnosis. Although Pneumonia is prevalent, detection and diagnosis are challenging. The deep learning network AlexNet was utilized through transfer learning. A dataset consisting of 11,318 images was used for training, and a preliminary diagnosis accuracy of 72% was achieved.

Improved Iterative Truncated Arithmetic Mean Filter, Prathyusha Surampudi Venkata

University of New Orleans Theses and Dissertations

This thesis discusses image processing and filtering techniques with emphasis on Mean filter, Median filter, and different versions of the Iterative Truncated Arithmetic Mean (ITM) filter. Specifically, we review in detail the ITM algorithms (ITM1 and ITM2) proposed by Xudong Jiang. Although filtering is capable of reducing noise in an image, it usually also results in smoothening or some other form of distortion of image edges and file details. Therefore, maintaining a proper trade off between noise reduction and edge/detail distortion is key. In this thesis, an improvement over Xudong Jiang’s ITM filters, namely ITM3, has been proposed and tested …

Real-Time Streaming Video And Image Processing On Inexpensive Hardware With Low Latency, Richard L. Gregg

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The use of resource constrained inexpensive hardware places restrictions on the design of streaming video and image processing system performance. In order to achieve acceptable frame-per-second (fps) performance with low latency, it is important to understand the response time requirements that the system needs to meet. For humans to be able to process and react to an image there should not be more than a 100ms delay between the time a camera captures an image and subsequently displays that image to the user.

In order to accomplish this goal, several design considerations need to be taken into account that limit …

Hybrid Single And Dual Pattern Structured Light Illumination, Minghao Wang

Theses and Dissertations--Electrical and Computer Engineering

Structured Light Illumination is a widely used 3D shape measurement technique in non-contact surface scanning. Multi-pattern based Structured Light Illumination methods reconstruct 3-D surface with high accuracy, but are sensitive to object motion during the pattern projection and the speed of scanning process is relatively long. To reduce this sensitivity, single pattern techniques are developed to achieve a high speed scanning process, such as Composite Pattern (CP) and Modified Composite Pattern (MCP) technique. However, most of single patter techniques have a significant banding artifact and sacrifice the accuracy. We focus on developing SLI techniques can achieve both high speed, high …

Atrengine: An Orientation-Based Algorithm For Automatic Target Recognition, Justin Ting-Jeuan Kuo

Master's Theses

Automatic Target Recognition (ATR) is a subject involving the use of sensor data to develop an algorithm for identifying targets of significance. It is of particular interest in military applications such as unmanned aerial vehicles and missile tracking systems. This thesis develops an orientation-based classification approach from previous ATR algorithms for 2-D Synthetic Aperture Radar (SAR) images. Prior work in ATR includes Chessa Guilas’ Hausdorff Probabilistic Feature Analysis Approach in 2005 and Daniel Cary’s Optimal Rectangular Fit in 2007.

A system incorporating multiple modules performing different tasks is developed to streamline the data processing of previous algorithms. Using images from …

Monitoring Civil Infrastructure Using Image Template Matching, Vikram Mukesh Patel

Boise State University Theses and Dissertations

Structural health monitoring (SHM) is an active area of research devoted to systems that can autonomously and proactively assess the structural integrity of civil structures. This thesis explores the possibility of monitoring civil structures using image template matching and low-cost embedded data acquisition. By acquiring several consecutive images of a structure, one can determine if movement in the structure has occurred. This information can be analyzed to determine long-term changes within a structure, which can then be used to proactively prioritize maintenance, reduce maintenance costs, and prevent structural failure. This will allow structures to be maintained based on objective data …