Physical Sciences and Mathematics Commons^™

Object Detection Using Contrast Enhancement And Dynamic Noise Reduction, Justin Lee Baker

UNLV Theses, Dissertations, Professional Papers, and Capstones

Edge detection is one of the most important steps a computer must perform to gain understanding of an object in a digital image either from disk or from video feed. Edge detection allows for the computer to describe the shape of the objects in an image and create a pixel boundary defining what is considered part of an object, and what is not. Cannys edge detection algorithm is one of the most robust and accurate of these edge detection algorithms. However, as with many algorithms in image processing, there are many cases where the algorithm does not perform as well …

Novel Color And Local Image Descriptors For Content-Based Image Search, Sugata Banerji

Dissertations

Content-based image classification, search and retrieval is a rapidly-expanding research area. With the advent of inexpensive digital cameras, cheap data storage, fast computing speeds and ever-increasing data transfer rates, millions of images are stored and shared over the Internet every day. This necessitates the development of systems that can classify these images into various categories without human intervention and on being presented a query image, can identify its contents in order to retrieve similar images.

Towards that end, this dissertation focuses on investigating novel image descriptors based on texture, shape, color, and local information for advancing content-based image search. Specifically, …

Real Time Pattern Recognition In Digital Video With Applications To Safety In Construction Sites, Dinesh Bajracharya

UNLV Theses, Dissertations, Professional Papers, and Capstones

In construction sites, various guidelines are provided for the correct use of safety equipment. Many fatalities and injuries occur to people because of the lack of exercise of these guidelines and proper monitoring of the violations. In order to improve these standards and amend the cause, a video based monitoring tool will be created for a construction site.

Based on the real time video obtained from cameras on the site, a classification algorithm will be created which has the intelligence to recognize if any safety rules have been violated. A classification vector will be created based on the different classifiers, …

Real Time Digital Night Vision Using Nonlinear Contrast Enhancement, Nishikar Sapkota

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis describes a nonlinear contrast enhancement technique to implement night vision in digital video. It is based on the global histogram equalization algorithm. First, the effectiveness of global histogram equalization is examined for images taken in low illumination environments in terms of Peak signal to noise ratio (PSNR) and visual inspection of images. Our analysis establishes the existence of an optimum intensity for which histogram equalization yields the best results in terms of output image quality in the context of night vision. Based on this observation, an incremental approach to histogram equalization is developed which gives better results than …

A Digital Image Processing Method For Detecting Pollution In The Atmosphere From Camera Video, Amrita Nikhil Amritphale

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this thesis we examine the use of digital cameras to detect the magnitude of atmospheric pollution present in the atmosphere. Digital cameras are inexpensive and are being used in countless areas, many of which are outdoors and very public. For example, we see digital cameras located at street intersections, city and state parks, and recreation areas. The theory presented in this paper could help agencies to monitor air quality at any of these sites. Our theory is based on certain molecules and particles that are present in clean air absorb, luminesce, refract, reflect, or scatter the red, green, and …

Integrated Development And Parallelization Of Automated Dicentric Chromosome Identification Software To Expedite Biodosimetry Analysis, Yanxin Li

Electronic Thesis and Dissertation Repository

Manual cytogenetic biodosimetry lacks the ability to handle mass casualty events. We present an automated dicentric chromosome identification (ADCI) software utilizing parallel computing technology. A parallelization strategy combining data and task parallelism, as well as optimization of I/O operations, has been designed, implemented, and incorporated in ADCI. Experiments on an eight-core desktop show that our algorithm can expedite the process of ADCI by at least four folds. Experiments on Symmetric Computing, SHARCNET, Blue Gene/Q multi-processor computers demonstrate the capability of parallelized ADCI to process thousands of samples for cytogenetic biodosimetry in a few hours. This increase in speed underscores the …

Impact Of Varied Low Resolution Phantoms On Intensity Modulated Proton Therapy Dose Distributions, Aarohi Shyam Padhye

Theses Digitization Project

The primary purpose of this thesis is to discuss the usefulness of image segmentation techniques in creating accurate proton dose distribution plans. The calculation of the proton dose distribution has to take into account the material (tissue, bone, brain) in the treatment area of the patients body.