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In most instances, multiple-modality visualization of pathologies will present advantages over single-modality studies. For many medical imaging procedures, it is desirable to produce a ldquofusedrdquo output that simultaneously exhibits characteristics of the data from each individual modality to reduce the difficulty of the decision-making process for radiologists. Preprocessing for most data fusion...
In this paper, we present different pattern recognition approaches for automatically detecting tear ducts in iris acquired eye images for enhancing iris recognition and detecting mislabeling in datasets. Detecting the tear duct in an image will tell an iris recognition system whether the presented eye image is that of a left or a right eye. This will enable the iris matcher to match the enrolled image...
We report on processing techniques to effectively control the data bandwidth in larger format focal plane array (FPA) sensors. We have developed an image processing architecture for foveating variable acuity FPAs that give a controlled reduction in the data rate via simple circuits that estimate activity on the FPA image plane. Integrated on-FPA signal processing goals are to perform pre-processing...
Traditionally, iris recognition is always about analyzing and extracting features from iris texture. We proposed to investigate regions around eyelashes and extract useful information which helps us to perform ethnic classification. We propose an algorithm which is easy to implement and effective. First, we locate eyelash region by using ASM to model eyelid boundary. Second, we extract local patch...
We present an agent-based full body tracking and 3D animation system to generate motion data using stereo calibrated cameras. The novelty of our approach is that agents are bound to body-part (bone structure) being tracked. These agents are autonomous, self-aware entities that are capable of communicating with other agents to perform tracking within agent coalitions. Each agent seeks for ldquoevidencerdquo...
Differentiating between normal human activity and aberrant behavior via closed circuit television cameras is a difficult and fatiguing task. The vigilance required of human observers when engaged in such tasks must remain constant, yet attention falls off dramatically over time. In this paper we propose an architecture for capturing data and creating a test and evaluation system to monitor video sensors...
In this paper, we present novel approaches of automatically detecting human faces in images which is extremely important for any face recognition system. This paper expands on the traditional Viola-Jones approach by proposing to boost a plethora of mixed feature sets for face detection; we do this by adding non-Haar-like elements to a large pool of mixed features in an Adaboost framework. We show...
Surveillance cameras are inexpensive and everywhere these days but the manpower required to monitor and analyze them is expensive. Consequently the videos from these cameras are usually monitored sparingly or not at all; they are often used merely as archive, to refer back to once an incident is known to have taken place. Surveillance cameras can be a far more useful tool if instead of passively recording...
One of the key problems of conventional iris recognition methods is that they are based on processing single iris image and require good image quality as an essential condition. These requisites entail considerable constraints on users for taking iris images. Video based iris recognition can provide convenience and time efficiency to the subjects with undemanding restrains during iris acquisition...
Face detection and recognition in a video is a challenging research topic as overall processes must be done timely and efficiently. In this paper, a novel face detection and recognition system using three fast cascade face verification modules and an ensemble classifier is presented. Firstly, the head of a tester is serially verified by our proposed three verification modules: face skin verification...
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