Browsing by Author "Du, Yingzi"

Now showing 1 - 6 of 6
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    Embedded System for Sensor Communication and Security
    (2010) An, Feng; Rizkalla, Maher; Li, Lingxi; Du, Yingzi; Salama, Paul; Knieser, Michael
    In this work, inter-integrated circuit mode (I2C) software was used to communicate between sensors and the embedded control system, utilizing PIC182585 MPLAB hardware. These sensors were built as part of a system on board that includes the sensors, microcontroller, and interface circuitry. The hardware includes the PIC18 processor, FPGA chip, and peripherals. A FPGA chip was used to interface the processor with the peripherals in order to operate at the same clock speed. This hardware design features high level of integration, reliability, high precision, and high speed communications. The software was first designed to operate each sensor separately, then the sensor system was integrated (to combine all sensors, microcontroller, and interfacing circuitries), and the software was updated to provide various actions if triggered by the sensors. Actions taken by the processor may include alarming signals that are based on threshold values received from the sensors, and inquiring temperature and CO2 readings. The system was designed for HVAC (heating, ventilating and air conditioning) applications and industrial settings. The overall system incorporating temperature and CO2 sensors was implemented and successfully tested. The response of the multi-sensor system was agreeable with the design parameters. The system may be expanded to include other sensors such as light senor, pressure sensor, etc. Monitoring the threshold values should add to the security features of the integrated communication system. This design features low power consumption (utilizing the sleeping mode of the processors), high speed communications, security, and flexibility to expansion.
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    Iris Recognition: The Consequences of Image Compression
    (SpringerOpen, 2010-04-26) Ives, Robert W.; Bishop, Daniel A.; Du, Yingzi; Belcher, Craig; Electrical and Computer Engineering, School of Engineering and Technology
    Iris recognition for human identification is one of the most accurate biometrics, and its employment is expanding globally. The use of portable iris systems, particularly in law enforcement applications, is growing. In many of these applications, the portable device may be required to transmit an iris image or template over a narrow-bandwidth communication channel. Typically, a full resolution image (e.g., VGA) is desired to ensure sufficient pixels across the iris to be confident of accurate recognition results. To minimize the time to transmit a large amount of data over a narrow-bandwidth communication channel, image compression can be used to reduce the file size of the iris image. In other applications, such as the Registered Traveler program, an entire iris image is stored on a smart card, but only 4 kB is allowed for the iris image. For this type of application, image compression is also the solution. This paper investigates the effects of image compression on recognition system performance using a commercial version of the Daugman iris2pi algorithm along with JPEG-2000 compression, and links these to image quality. Using the ICE 2005 iris database, we find that even in the face of significant compression, recognition performance is minimally affected.
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    A New Approach for Cancelable Iris Recognition
    (Office of the Vice Chancellor for Research, 2010-04-09) Yang, Kai; Yan, Sui; Zhou, Zhi; Du, Yingzi; Zou, Xukai; Orr, Scott
    The iris is a stable and reliable biometric for positive human identification. However, the traditional iris recognition scheme raises several privacy concerns. One’s iris pattern is permanently bound with him and cannot be changed. Hence, once it is stolen, this biometric is lost forever as well as all the applications where this biometric is used. Thus, new methods are desirable to secure the original pattern and ensure its revocability and alternatives when compromised. In this paper, we propose a novel scheme which incorporates iris features, noninvertible transformation and data encryption to achieve “cancelability” and at the same time increases iris recognition accuracy.
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    A NEW APPROACH FOR HUMAN IDENTIFICATION USING THE EYE
    (2010) Thomas, N. Luke; Du, Yingzi; Rizkalla, Maher; King, Brian
    The vein structure in the sclera, the white and opaque outer protective covering of the eye, is anecdotally stable over time and unique to each person. As a result, it is well suited for use as a biometric for human identification. A few researchers have performed sclera vein pattern recognition and have reported promising, but low accuracy, initial results. Sclera recognition poses several challenges: the vein structure moves and deforms with the movement of the eye and its surrounding tissues; images of sclera patterns are often defocused and/or saturated; and, most importantly, the vein structure in the sclera is multi-layered and has complex non-linear deformation. The previous approaches in sclera recognition have treated the sclera patterns as a one-layered vein structure, and, as a result, their sclera recognition accuracy is not high. In this thesis, we propose a new method for sclera recognition with the following contributions: First, we developed a color-based sclera region estimation scheme for sclera segmentation. Second, we designed a Gabor wavelet based sclera pattern enhancement method, and an adaptive thresholding method to emphasize and binarize the sclera vein patterns. Third, we proposed a line descriptor based feature extraction, registration, and matching method that is scale-, orientation-, and deformation-invariant, and can mitigate the multi-layered deformation effects and tolerate segmentation error. It is empirically verified using the UBIRIS and IUPUI multi-wavelength databases that the proposed method can perform accurate sclera recognition. In addition, the recognition results are compared to iris recognition algorithms, with very comparable results.
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    A Review of Unsupervised Spectral Target Analysis for Hyperspectral Imagery
    (SpringerOpen, 2010-04-08) Chang, Chein-I; Jiao, Xiaoli; Wu, Chao-Cheng; Du, Yingzi; Chang, Mann-Li; Electrical and Computer Engineering, School of Engineering and Technology
    One of great challenges in unsupervised hyperspectral target analysis is how to obtain desired knowledge in an unsupervised means directly from the data for image analysis. This paper provides a review of unsupervised target analysis by first addressing two fundamental issues, "what are material substances of interest, referred to as targets?" and "how can these targets be extracted from the data?" and then further developing least squares (LS)-based unsupervised algorithms for finding spectral targets for analysis. In order to validate and substantiate the proposed unsupervised hyperspectral target analysis, three applications in endmember extraction, target detection and linear spectral unmixing are considered where custom-designed synthetic images and real image scenes are used to conduct experiments.
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    Scale Invariant Gabor Descriptor-Based Noncooperative Iris Recognition
    (SpringerOpen, 2010-04-28) Du, Yingzi; Belcher, Craig; Zhou, Zhi; Electrical and Computer Engineering, School of Engineering and Technology
    A new noncooperative iris recognition method is proposed. In this method, the iris features are extracted using a Gabor descriptor. The feature extraction and comparison are scale, deformation, rotation, and contrast-invariant. It works with off-angle and low-resolution iris images. The Gabor wavelet is incorporated with scale-invariant feature transformation (SIFT) for feature extraction to better extract the iris features. Both the phase and magnitude of the Gabor wavelet outputs were used in a novel way for local feature point description. Two feature region maps were designed to locally and globally register the feature points and each subregion in the map is locally adjusted to the dilation/contraction/deformation. We also developed a video-based non-cooperative iris recognition system by integrating video-based non-cooperative segmentation, segmentation evaluation, and score fusion units. The proposed method shows good performance for frontal and off-angle iris matching. Video-based recognition methods can improve non-cooperative iris recognition accuracy.