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Non-Invasive Sensors™
The Company is developing a family of photo-detectors that have a structure eminently suitable for non-invasive monitoring of physiological analytes in-vivo, specifically, blood glucose. We are developing a family of smart analog vision chips and ancillary software capable to adaptively select image processing parameters and regions of interest in the field of view. This family of devices is highly relevant to our approach to real-time control and prediction of biological processes, because it can be configured to embed prior knowledge algorithms to perform image pre-selection.
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Centroid computation in W&S: When an electron cloud lands on the pattern, if collected charges QS, QW are as shown, and Q0 for the substrate, the (X,Y) coordinates of the centroid can be computed with the simple formulas:
X = 2.QS / (QS + QW + Q0) |
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The research phase of this project was sponsored by ARPA/BMDO/IST and managed by the US Army Space and Missile Defense Command, Huntsville, Alabama. The Advanced Devices and Applications Group at Sandia National Laboratories (Processing and Prototyping Group) implemented the innovative device solutions which led to 6-inch active area prototype W&S wafers: yes, you read that right - six inch active area.
For more information about our work, please consult SPIE
Proceedings Vol. 3234:
Design and Manufacturing of WDM DevicesEditor(s): Ray T. Chen, Univ. of Texas/Austin, Austin, TX, USA;
Louis S. Lome, Ballistic Missile Defense Organization, Arlington, VA,
USA. ISBN: 0-8194-2667-9, 238 pages Published 1998 |
Paper #: 3234-21
Efficient imaging with integrated optoelectronics: I. Overview and some
applications, pp.184-191 Author(s): Aureliu M. Porumbescu, Array
Vision Engineering Co., Alachua, FL, USA; Gerhard X. Ritter, Univ. of
Florida, Gainesville, FL, USA; Mark S. Schmalz, Univ. of
Florida, Gainesville, FL, USA; Joseph N. Wilson, Univ. of Florida,
Gainesville, FL, USA; Vincent M. Hietala, Sandia National Labs.,
Albuquerque, NM, USA; James G. Fleming, Sandia National Labs.,
Albuquerque, NM, USA.
Abstract: We report on AVE's research on a new family of smart
analog vision chips and ancillary software capable to adaptively select
image processing parameters and regions of interest in the field of view.
The project aims to adapt the wedge- and-strip (WS) position-sensitive
configuration to real- time, multi-object detection. To that end, we use
semiconductor WS detector (WESD) arrays with spatial prefiltering
implemented via image algebra. The WESD have the ability to
locate the centroid of an incident light spot and, with appropriate
prefiltering, to locate the centroids of multiple light spots. A unique
analog mode centroid computation scheme facilitates on-chip data
processing, while an overall undemanding geometry simplify electronics
fabrication. Based on results of preliminary design and analysis, very
significant cost reductions over existing massively parallel vision
processors are foreseen. Superior optical resolution results even when the
sensor is manufactured with 'coarse line width' semiconductor
processing technology, which may lead to detectors with large
photosensitive areas. Departing from photo-sensitive element
miniaturization provides the opportunity to launch a new class of vision
chips, with active area limited only by the semiconductor wafer size used
to manufacture the array. We suggest several applications of this new
technology, including an efficient and robust WDM demultiplexing device.
Paper #: 3234-29
Efficient imaging with integrated optoelectronics: II. Massively
parallel analog vision chip, pp.192-205 Author(s): Mark S.
Schmalz, Univ. of Florida, Gainesville, FL, USA; Gerhard X. Ritter, Univ.
of Florida, Gainesville, FL, USA; Joseph N. Wilson, Univ. of
Florida, Gainesville, FL, USA; Aureliu M. Porumbescu, Array Vision
Engineering Co., Alachua, FL, USA.
Abstract: Real-time multi-object detection has been an elusive goal
of automated target recognition (ATR) scenarios that employ on- board
millimeter-scale processors at low light levels and reduced power
requirements. This paper discusses an adaptation of the wedge-and -strip
anode to yield design analyses for a silicon wedge-and-strip detector (WESD).
In practice, a WESD could compute the centroid of an incident light-spot
and, with appropriate prefiltering can locate centroids of multiple
light-spots. Due to on-chip processing and a nondemanding geometry, the
WESD approach drastically reduces electronics fabrication complexity and
cost. Based on results of preliminary design and analysis, significant
cost reductions over existing massively parallel vision processors (MPVPs)
are foreseen for object location via centroid computation. Algorithms and
simulations are expressed in image algebra, a rigorous, concise,
computationally complete notation that unifies linear and nonlinear
mathematics in the image domain. Developed at University of Florida over
the past decade, image algebra is a unifying language for image and signal
processing that has been implemented on numerous workstations and parallel
computers. Thus, our algorithms are rigorous and widely portable. Circuit
analysis emphasizes effects of capacitance and electrode configuration on
WESD spatial resolution. Simulation results show that the WESD has
centroid computation accuracy comparable to equivalent-resolution array
detectors supported by on-board MPVPs. Additional technical discussion
pertains to the feasibility of space- division multiplexing for
multi-object detection and location at video rates.
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