Comparison of Computer-Based and Optical Face Recognition Paradigms

The main objectives of this thesis are to validate an improved principal components analysis (IPCA) algorithm on images; designing and simulating a digital model for image compression, face recognition and image detection by using a principal components analysis (PCA) algorithm and the IPCA algorithm; designing and simulating an optical model for face recognition and object detection by using the joint transform correlator (JTC); establishing detection and recognition thresholds for each model; comparing between the performance of the PCA algorithm and the performance of the IPCA algorithm in compression, recognition and, detection; and comparing between the performance of the digital model and the performance of the optical model in recognition and detection. The MATLAB © software was used for simulating the models. PCA is a technique used for identifying patterns in data and representing the data in order to highlight any similarities or differences. The identification of patterns in data of high dimensions (more than three dimensions) is too difficult because the graphical representation of data is impossible. Therefore, PCA is a powerful method for analyzing data. IPCA is another statistical tool for identifying patterns in data. It uses information theory for improving PCA. The joint transform correlator (JTC) is an optical correlator used for synthesizing a frequency plane filter for coherent optical systems. The IPCA algorithm, in general, behaves better than the PCA algorithm in the most of the applications. It is better than the PCA algorithm in image compression because it obtains higher compression, more accurate reconstruction, and faster processing speed with acceptable errors; in addition, it is better than the PCA algorithm in real-time image detection due to the fact that it achieves the smallest error rate as well as remarkable speed. On the other hand, the PCA algorithm performs better than the IPCA algorithm in face recognition because it offers an acceptable error rate, easy calculation, and a reasonable speed. Finally, in detection and recognition, the performance of the digital model is better than the performance of the optical model.

COMPRESSION BEHAVIOR AT HIGH STRAIN RATE FOR AN ULTRA HIGH PERFORMANCE CONCRETE

The need for a stronger and more durable building material is becoming more important as the structural engineering field expands and challenges the behavioral limits of current materials. One of the demands for stronger material is rooted in the effects that dynamic loading has on a structure. High strain rates on the order of 101 s-1 to 103 s-1, though a small part of the overall types of loading that occur anywhere between 10-8 s-1 to 104 s-1 and at any point in a structures life, have very important effects when considering dynamic loading on a structure. High strain rates such as these can cause the material and structure to behave differently than at slower strain rates, which necessitates the need for the testing of materials under such loading to understand its behavior. Ultra high performance concrete (UHPC), a relatively new material in the U.S. construction industry, exhibits many enhanced strength and durability properties compared to the standard normal strength concrete. However, the use of this material for high strain rate applications requires an understanding of UHPC’s dynamic properties under corresponding loads. One such dynamic property is the increase in compressive strength under high strain rate load conditions, quantified as the dynamic increase factor (DIF). This factor allows a designer to relate the dynamic compressive strength back to the static compressive strength, which generally is a well-established property. Previous research establishes the relationships for the concept of DIF in design. The generally accepted methodology for obtaining high strain rates to study the enhanced behavior of compressive material strength is the split Hopkinson pressure bar (SHPB). In this research, 83 Cor-Tuf UHPC specimens were tested in dynamic compression using a SHPB at Michigan Technological University. The specimens were separated into two categories: ambient cured and thermally treated, with aspect ratios of 0.5:1, 1:1, and 2:1 within each category. There was statistically no significant difference in mean DIF for the aspect ratios and cure regimes that were considered in this study. DIF’s ranged from 1.85 to 2.09. Failure modes were observed to be mostly Type 2, Type 4, or combinations thereof for all specimen aspect ratios when classified according to ASTM C39 fracture pattern guidelines. The Comite Euro-International du Beton (CEB) model for DIF versus strain rate does not accurately predict the DIF for UHPC data gathered in this study. Additionally, a measurement system analysis was conducted to observe variance within the measurement system and a general linear model analysis was performed to examine the interaction and main effects that aspect ratio, cannon pressure, and cure method have on the maximum dynamic stress.