A high efficient biometrics approach for unconstrained iris segmentation and recognition

This dissertation develops an innovative approach towards less-constrained iris biometrics. Two major contributions are made in this research endeavor: (1) Designed an award-winning segmentation algorithm in the less-constrained environment where image acquisition is made of subjects on the move and taken under visible lighting conditions, and (2) Developed a pioneering iris biometrics method coupling segmentation and recognition of the iris based on video of moving persons under different acquisitions scenarios. The first part of the dissertation introduces a robust and fast segmentation approach using still images contained in the UBIRIS (version 2) noisy iris database. The results show accuracy estimated at 98% when using 500 randomly selected images from the UBIRIS.v2 partial database, and estimated at 97% in a Noisy Iris Challenge Evaluation (NICE.I) in an international competition that involved 97 participants worldwide involving 35 countries, ranking this research group in sixth position. This accuracy is achieved with a processing speed nearing real time. The second part of this dissertation presents an innovative segmentation and recognition approach using video-based iris images. Following the segmentation stage which delineates the iris region through a novel segmentation strategy, some pioneering experiments on the recognition stage of the less-constrained video iris biometrics have been accomplished. In the video-based and less-constrained iris recognition, the test or subject iris videos/images and the enrolled iris images are acquired with different acquisition systems. In the matching step, the verification/identification result was accomplished by comparing the similarity distance of encoded signature from test images with each of the signature dataset from the enrolled iris images. With the improvements gained, the results proved to be highly accurate under the unconstrained environment which is more challenging. This has led to a false acceptance rate (FAR) of 0% and a false rejection rate (FRR) of 17.64% for 85 tested users with 305 test images from the video, which shows great promise and high practical implications for iris biometrics research and system design.

Soft power as the new norm: How the Chinese-Russian strategic partnership (soft) balances American hegemony in an era of unipolarity

This study explores how great powers not allied with the United States formulate their grand strategies in a unipolar international system. Specifically, it analyzes the strategies China and Russia have developed to deal with U.S. hegemony by examining how Moscow and Beijing have responded to American intervention in Central Asia. The study argues that China and Russia have adopted a soft balancing strategy of to indirectly balance the United States at the regional level. This strategy uses normative capabilities such as soft power, alternative institutions and regionalization to offset the overwhelming material hardware of the hegemon. The theoretical and methodological approach of this dissertation is neoclassical realism. Chinese and Russian balancing efforts against the United States are based on their domestic dynamics as well as systemic constraints. Neoclassical realism provides a bridge between the internal characteristics of states and the environment which those states are situated. Because China and Russia do not have the hardware (military or economic power) to directly challenge the United States, they must resort to their software (soft power and norms) to indirectly counter American preferences and set the agenda to obtain their own interests. Neoclassical realism maintains that soft power is an extension of hard power and a reflection of the internal makeup of states. The dissertation uses the heuristic case study method to demonstrate the efficacy of soft balancing. Such case studies help to facilitate theory construction and are not necessarily the demonstrable final say on how states behave under given contexts. Nevertheless, it finds that China and Russia have increased their soft power to counterbalance the United States in certain regions of the world, Central Asia in particular. The conclusion explains how soft balancing can be integrated into the overall balance-of-power framework to explain Chinese and Russian responses to U.S. hegemony. It also suggests that an analysis of norms and soft power should be integrated into the study of grand strategy, including both foreign policy and military doctrine.

Thermal imaging as a biometrics approach to facial signature authentication

This dissertation develops an image processing framework with unique feature extraction and similarity measurements for human face recognition in the thermal mid-wave infrared portion of the electromagnetic spectrum. The goals of this research is to design specialized algorithms that would extract facial vasculature information, create a thermal facial signature and identify the individual. The objective is to use such findings in support of a biometrics system for human identification with a high degree of accuracy and a high degree of reliability. This last assertion is due to the minimal to no risk for potential alteration of the intrinsic physiological characteristics seen through thermal infrared imaging. The proposed thermal facial signature recognition is fully integrated and consolidates the main and critical steps of feature extraction, registration, matching through similarity measures, and validation through testing our algorithm on a database, referred to as C-X1, provided by the Computer Vision Research Laboratory at the University of Notre Dame. Feature extraction was accomplished by first registering the infrared images to a reference image using the functional MRI of the Brain’s (FMRIB’s) Linear Image Registration Tool (FLIRT) modified to suit thermal infrared images. This was followed by segmentation of the facial region using an advanced localized contouring algorithm applied on anisotropically diffused thermal images. Thermal feature extraction from facial images was attained by performing morphological operations such as opening and top-hat segmentation to yield thermal signatures for each subject. Four thermal images taken over a period of six months were used to generate thermal signatures and a thermal template for each subject, the thermal template contains only the most prevalent and consistent features. Finally a similarity measure technique was used to match signatures to templates and the Principal Component Analysis (PCA) was used to validate the results of the matching process. Thirteen subjects were used for testing the developed technique on an in-house thermal imaging system. The matching using an Euclidean-based similarity measure showed 88% accuracy in the case of skeletonized signatures and templates, we obtained 90% accuracy for anisotropically diffused signatures and templates. We also employed the Manhattan-based similarity measure and obtained an accuracy of 90.39% for skeletonized and diffused templates and signatures. It was found that an average 18.9% improvement in the similarity measure was obtained when using diffused templates. The Euclidean- and Manhattan-based similarity measure was also applied to skeletonized signatures and templates of 25 subjects in the C-X1 database. The highly accurate results obtained in the matching process along with the generalized design process clearly demonstrate the ability of the thermal infrared system to be used on other thermal imaging based systems and related databases. A novel user-initialization registration of thermal facial images has been successfully implemented. Furthermore, the novel approach at developing a thermal signature template using four images taken at various times ensured that unforeseen changes in the vasculature did not affect the biometric matching process as it relied on consistent thermal features.

The Impact of Hurricane Georges on Soft-Bottom, Back Reef Communitites: Site- and Species-Specific Effects in South Florida Seagrass Beds

Seagrass beds are the dominant benthic marine communities in the back reef environment of the Florida Keys. At a network of 30 permanent monitoring stations in this back reef environment, the seagrass Thalassia testudinum Banks & Soland. ex Koenig was the most common marine macrophyte, but the seagrasses Syringodium fi liforme Kuetz., and Halodule wrightii Aschers., as well as many taxa of macroalgae, were also commonly encountered. The calcareous green macroalgae, especially Halimeda spp. and Penicillus spp., were the most common macroalgae. The passage of Hurricane Georges on September 25, 1998 caused an immediate loss of 3% of the density of T. testudinum, compared to 19% of the S. fi liforme and 24% of the calcareous green algae. The seagrass beds at three of the stations were completely obliterated by the storm. Stations that had little to moderate sediment deposition recovered from the storm within 1 yr, while the station buried by 50 cm of sediment and the two stations that experienced substantial erosion had recovered very little during the 3 yrs after the storm. Early colonizers to these severely disturbed sites were calcareous green algae. Hurricanes may increase benthic macrophyte diversity by creating disturbed patches with the landscape, but moderate storm disturbance may actually reduce macrophyte diversity by removing the early successional species from mixed-species seagrass beds.

Biometrics for Hospitality and Tourism: A New Wave of Information Technology

The technologies that empower biometrics have been around for a number of years, but until recently these technologies have been viewed as exotic. In the not too distant future biometrics will be used to regulate internal processes and to improve services in the hospitality and tourism industries. This paper provides an understanding of the current use of biometrics in general and its practical value for the future in hospitality and tourism. The study presents a review of current practices of biometrics with special reference to the hospitality and tourism businesses, addresses key issues imposed by this technology, and identifies business and marketing implications for these industries.