Recognition of Eye Characteristics

This chapter deals with the recognition of features contained within the human eye, namely the iris and retina. The great advantage is that both the iris and retina contain a large amount of information, that is, they can be used for a larger group of users. The disadvantage, on the other hand, is the fear from users in regard to possible eye injury. Both of these features cannot be easily acquired and misused to cheat a biometric system. This chapter also explains how to capture and process these two biometric characteristics. However, the number of biometric industrial solutions dealing with retina recognition is very limited—it is practically not possible to find an available biometric device for identity recognition on the market based on this biometric characteristic

Recognition of Eye Characteristics

Children grow and develop in a life colored by the violation of others right, crime, compulsion, ignorance, unclearness between right and wrong, good and bad, allowed and not allowed behaviors. Building moral intelligence is very important to do in order that the childrens intuition is able to differentiate the right and the wrong. Thus, they can reject the bad influences from outside. One of the ways used to give moral value to the children is sociodrama.The research aims to know the sociodrama method in improving the moral intelligence of children. Subject of the research is the student of elementary school. The number of subject in the experiment and control groups is same that is 14 students.The research is design using model of The Untreated Control Group Design with Pretest and Posttest. The design uses two groups examined which consist of an experiment group and a control group. The measurement is conducted twice using moral intelligence measurement instrument, namely before it is given treatment (pre-test) and after it has been given treatment (post-test).The result of analysis using T-Test shows that there is a difference of moral intelligence achievement level of the children between those who receive moral value guidance through sociodrama method and those who do not receive moral value guidance through sociodrama method p = 0,009 (p<0,05). The result of analysis also shows that there is difference of moral intelligence achievement level of th children before receiving moral value guidance through sociodrama method and after they have receive the moral value guidance through sociodrama method p = 0,033 (p<0,05). The result of analysis shows the great contribution of sociodrama method towards the moral intelligence of children is 30,9%

Multibiometric System Combining Iris and Retina

Tato diplomová práce se zabývá multibiometrickými systémy, specificky potom biometrickou fúzí. Práce popisuje biometrii oka, tedy rozpoznávání na základě sítnice a duhovky. Stěžejní část tvoří návrh a implementace biometrického systému, který je založený na rozpoznání sítnice a duhovky.This diploma thesis focuses on multibiometric systems, specifically on biometric fusion. The thesis describes eye biometrics, i.e. recognition based on retina and iris. The key part consists of design and implementation specification of a biometric system based on retina and iris recognition.

Human operator performance of remotely controlled tasks: Teleoperator research conducted at NASA's George C. Marshal Space Flight Center

The capabilities within the teleoperator laboratories to perform remote and teleoperated investigations for a wide variety of applications are described. Three major teleoperator issues are addressed: the human operator, the remote control and effecting subsystems, and the human/machine system performance results for specific teleoperated tasks

3D head motion, point-of-regard and encoded gaze fixations in real scenes: next-generation portable video-based monocular eye tracking

Portable eye trackers allow us to see where a subject is looking when performing a natural task with free head and body movements. These eye trackers include headgear containing a camera directed at one of the subject\u27s eyes (the eye camera) and another camera (the scene camera) positioned above the same eye directed along the subject\u27s line-of-sight. The output video includes the scene video with a crosshair depicting where the subject is looking -- the point-of-regard (POR) -- that is updated for each frame. This video may be the desired final result or it may be further analyzed to obtain more specific information about the subject\u27s visual strategies. A list of the calculated POR positions in the scene video can also be analyzed. The goals of this project are to expand the information that we can obtain from a portable video-based monocular eye tracker and to minimize the amount of user interaction required to obtain and analyze this information. This work includes offline processing of both the eye and scene videos to obtain robust 2D PORs in scene video frames, identify gaze fixations from these PORs, obtain 3D head motion and ray trace fixations through volumes-of-interest (VOIs) to determine what is being fixated, when and where (3D POR). To avoid the redundancy of ray tracing a 2D POR in every video frame and to group these POR data meaningfully, a fixation-identification algorithm is employed to simplify the long list of 2D POR data into gaze fixations. In order to ray trace these fixations, the 3D motion -- position and orientation over time -- of the scene camera is computed. This camera motion is determined via an iterative structure and motion recovery algorithm that requires a calibrated camera and knowledge of the 3D location of at least four points in the scene (that can be selected from premeasured VOI vertices). The subjects 3D head motion is obtained directly from this camera motion. For the final stage of the algorithm, the 3D locations and dimensions of VOIs in the scene are required. This VOI information in world coordinates is converted to camera coordinates for ray tracing. A representative 2D POR position for each fixation is converted from image coordinates to the same camera coordinate system. Then, a ray is traced from the camera center through this position to determine which (if any) VOI is being fixated and where it is being fixated -- the 3D POR in the world. Results are presented for various real scenes. Novel visualizations of portable eye tracker data created using the results of our algorithm are also presented

Detection and Classification of Diabetic Retinopathy Pathologies in Fundus Images

Diabetic Retinopathy (DR) is a disease that affects up to 80% of diabetics around the world. It is the second greatest cause of blindness in the Western world, and one of the leading causes of blindness in the U.S. Many studies have demonstrated that early treatment can reduce the number of sight-threatening DR cases, mitigating the medical and economic impact of the disease. Accurate, early detection of eye disease is important because of its potential to reduce rates of blindness worldwide. Retinal photography for DR has been promoted for decades for its utility in both disease screening and clinical research studies. In recent years, several research centers have presented systems to detect pathology in retinal images. However, these approaches apply specialized algorithms to detect specific types of lesion in the retina. In order to detect multiple lesions, these systems generally implement multiple algorithms. Furthermore, some of these studies evaluate their algorithms on a single dataset, thus avoiding potential problems associated with the differences in fundus imaging devices, such as camera resolution. These methodologies primarily employ bottom-up approaches, in which the accurate segmentation of all the lesions in the retina is the basis for correct determination. A disadvantage of bottom-up approaches is that they rely on the accurate segmentation of all lesions in order to measure performance. On the other hand, top-down approaches do not depend on the segmentation of specific lesions. Thus, top-down methods can potentially detect abnormalities not explicitly used in their training phase. A disadvantage of these methods is that they cannot identify specific pathologies and require large datasets to build their training models. In this dissertation, I merged the advantages of the top-down and bottom-up approaches to detect DR with high accuracy. First, I developed an algorithm based on a top-down approach to detect abnormalities in the retina due to DR. By doing so, I was able to evaluate DR pathologies other than microaneurysms and exudates, which are the main focus of most current approaches. In addition, I demonstrated good generalization capacity of this algorithm by applying it to other eye diseases, such as age-related macular degeneration. Due to the fact that high accuracy is required for sight-threatening conditions, I developed two bottom-up approaches, since it has been proven that bottom-up approaches produce more accurate results than top-down approaches for particular structures. Consequently, I developed an algorithm to detect exudates in the macula. The presence of this pathology is considered to be a surrogate for clinical significant macular edema (CSME), a sight-threatening condition of DR. The analysis of the optic disc is usually not taken into account in DR screening systems. However, there is a pathology called neovascularization that is present in advanced stages of DR, making its detection of crucial clinical importance. In order to address this problem, I developed an algorithm to detect neovascularization in the optic disc. These algorithms are based on amplitude-modulation and frequency-modulation (AM-FM) representations, morphological image processing methods, and classification algorithms. The methods were tested on a diverse set of large databases and are considered to be the state-of the art in this field

A Parametric Model for the Analysis and Quantification of Foveal Shapes

Recently, the advance of OCT enables a detailed examination of the human retina in-vivo for clinical routine and experimental eye research. One of the structures inside the retina of immense scientific interest is the fovea, a small retinal pit located in the central region with extraordinary visual resolution. Today, only a few investigations captured foveal morphology based on a large subject group by a detailed analysis employing mathematical models. In this work, we develop a parametric model function to describe the shape of the human fovea. Starting with a detailed discussion on the history and present of fovea research, we define the requirements for a suitable model and derive a function which can represent a broad range of foveal shapes. The model is one-dimensional in its basic form and can only account for the shape of one particular section through a fovea. Therefore, we apply a radial fitting scheme in different directions which can capture a fovea in its full three-dimensional appearance. Highly relevant foveal characteristics, derived from the model, provide valuable descriptions to quantify the fovea and allow for a detailed analysis of different foveal shapes. To put the theoretical model into practice, we develop a numerical scheme to compute model parameters from retinal \ac{oct} scans and to reconstruct the shape of an entire fovea. For the sake of scientific reproducibility, this section includes implementation details, examples and a discussion of performance considerations. Finally, we present several studies which employed the fovea model successfully. A first feasibility study verifies that the parametric model is suitable for foveal shapes occurring in a large set of healthy human eyes. In a follow-up investigation, we analyse foveal characteristics occurring in healthy humans in detail. This analysis will concern with different aspects including, e.g. an investigation of the fovea's asymmetry, a gender comparison, a left versus right eye correlation and the computation of subjects with extreme foveal shapes. Furthermore, we will show how the model was used to support investigations unrelated to the direct quantification of the fovea itself. In these investigations we employed the model to compute anatomically correct regions of interest in an analysis of the OCB and the calculation of an average fovea for an optical simulation of light rays. We will conclude with currently unpublished data that shows the fovea modelling of hunting birds which have unusual, funnel-like foveal shapes

An Augmentative Gaze Directing Framework for Multi-Spectral Imagery

Modern digital imaging techniques have made the task of imaging more prolic than ever and the volume of images and data available through multi-spectral imaging methods for exploitation is exceeding that which can be solely processed by human beings. The researchers proposed and developed a novel eye movement contingent framework and display system through adaption of the demonstrated technique of subtle gaze direction by presenting modulations within the displayed image. The system sought to augment visual search task performance of aerial imagery by incorporating multi-spectral image processing algorithms to determine potential regions of interest within an image. The exploratory work conducted was to study the feasibility of visual gaze direction with the specic intent of extending this application to geospatial image analysis without need for overt cueing to areas of potential interest and thereby maintaining the benefits of an undirected and unbiased search by an observer