Recently, the iris of the human eye has been used as a biometric indicator for identification. We have witnessed wide-scale
deployment of iris technology across many product categories. However, these iris recognition solutions do not
reflect the full potential of the technology. The robustness of the standoff iris segmentation approach relies heavily on
accurate iris segmentation techniques. Computing iris features requires a high quality segmentation process that focuses
on the subject's iris and properly extracts its boundaries. Because iris segmentation is sensitive to the acquisition
conditions, it is a very challenging problem. In this paper, we describe a standoff iris recognition system to identify non-cooperative
subjects. We introduce a novel iris segmentation approach that takes the analysis of edges into the polar
domain at an earlier stage and uses non-iterative polar differential operator to locate the inner and outer borders of the
iris. The approach is proven to be very effective for non-ideal gazed and obscured irises while providing comparable
results to top performing algorithms on frontal iris images.
The objective of this work was to determine the feasibility and reliability of using the moire interference phenomenon as a means to detect human intrusion within a monitored zone. We applied moire interference principle for use in low-cost, safety-critical industrial monitoring applications. Moire interference is usually applied in the context of industrial applications for shape measurements. In this framework, we show how we can apply this concept to build a new safety product that detects human intrusion into dangerous areas on the factory floor. We demonstrate that a solution based on moire interference offers the potential for detection true 3D objects while preventing false alarms due to lighting variations or shadows and simplifying the image processing software. In addition, our prosed approach is advantageous in the product certification process because it is an active detection method.
Reductions in Navy maintenance budgets and available personnel have dictated the need to transition from time-based to 'condition-based' maintenance. Achieving this will require new enabling diagnostic technologies. One such technology, the use of acoustic emission for the early detection of helicopter rotor head dynamic component faults, has been investigated by Honeywell Technology Center for its rotor acoustic monitoring system (RAMS). This ambitious, 38-month, proof-of-concept effort, which was a part of the Naval Surface Warfare Center Air Vehicle Diagnostics System program, culminated in a successful three-week flight test of the RAMS system at Patuxent River Flight Test Center in September 1997. The flight test results demonstrated that stress-wave acoustic emission technology can detect signals equivalent to small fatigue cracks in rotor head components and can do so across the rotating articulated rotor head joints and in the presence of other background acoustic noise generated during flight operation. This paper presents the results of stress wave data analysis of the flight-test dataset using wavelet-based techniques to assess background operational noise vs. machinery failure detection results.
KEYWORDS: Clocks, Calibration, Signal processing, Transistors, CMOS technology, Head, Head-mounted displays, Signal generators, Sensors, Control systems design
This paper describes the design of a clock generation circuitry to be used as part of an affordable gigabit module head mounted display. A self-calibrated tapped delay line is used to generate different clock signals, which are then passed through logical function to produce an integral- multiple of an input clock. The system is fabricated on 0.8 micrometers CMOS triple layer using MOSIS CMOS process. All processes technology can operate at 3.3 V or 5.0 V. Experimental results show a realization of 4 times clock multiplier circuit with an output range of up to 370 MHz with almost zero-clock skew. The proposed clock multiplier circuitry is simple, temperature independent, uses a very small number of transistors and hence requires less area and power dissipation than earlier realizations.
This paper presents an ATR design paradigm that self configures and adapts to the diverse scenarios encountered during a mission. Today's ATR is constructed via inefficient and sub-optimal system configuration and training, whose process is very labor intensive, subjective and inaccurate. The resulting ATR is only capable of a limited amount of adaptation to changes in the environment. Moreover, the operation of such ATR systems require a user with expert algorithmic knowledge. Addressing the above-mentioned problems, the Honeywell effort is producing a self-adaptive ATR system. The system employs a Genetic Algorithm to autonomously and optimally perform configuration and training; the system also includes a specific knowledge capture mechanism, the Context Capture tool, which ties the context of the mission with an optimal configuration. Lastly, the system employs Case Based Reasoning to dynamically configure and control the ATR system based on the changing context during an ATR mission.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.