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Adaptive Optoelectronic Eyes

Designs of "smart" cameras would be inspired by biological vision systems.

Aprogram of research has built a technological foundation for further development of systems that could be characterized, variously, as "smart" cameras or adaptive optoelectronic eyes. A system according to this concept would function in an optimal manner to capture images under a variety of lighting conditions and would be capable of semi-autonomous recognition of objects.

The approach taken in this research was to combine advances in understanding of the mechanisms of biological vision systems with advances in hybrid electronic/photonic packaging technology in order to develop algorithms, architectures, and optical and electronic hardware components and subsystems essential to building artificial, biologically inspired vision systems.

A primary goal of this research was to enable the development of a sensor/processor module (1) in which the sensor and processor would be intimately coupled and (2) that would have architectural characteristics and capabilities similar to those of the multilayer retina and early stages of vision in a mammalian visual system. The module would be a compact, multilayer, vertically integrated structure, containing very-large-scale integrated (VLSI) circuit chips. It would perform both sensing (image-acquisition) and processing functions (for purposes of extraction of features and recognition of objects, for example).

Multiple VLSI Chips having electronic and photonic functionalities would be stacked in a three-dimensional structure to construct a densely integrated hybrid electronic/photonic multichip module.
The upper part of the figure illustrates the basic architectural concept for a densely integrated hybrid electronic/ photonic multichip module. Dense arrays of fan-out and fan-in interconnections between layers would be implemented with the help of diffractive optical elements. Each layer other than the sensor layer would comprise or include a two-dimensional array of processing elements corresponding to the pixels of the sensor layer. Each processing element might include, for example, (1) analog neuron-like signal-processing circuitry, (2) analog-to-digital converter (sampleand- hold) circuitry, and/or (3) digital circuitry (for local memory, communication between neighboring pixels, and/or control). Other circuitry in each layer also might include (1) analog, digital, or hybrid analog/digital processors; (2) shifting circuitry for lateral scrolling functions; and (3) in the case of the sensor layer, photodetectors and preamplifier circuitry.

The lower part of the figure presents an enlarged view of the portion highlighted by the rectangle in the upper part of the figure, showing an example of dense optical fan-out/fan-in interconnections between layers in the multichip module. Each pixel of the lower silicon VLSI chip would contain both processing electronic circuitry and a photodetector illuminated with image-bearing or other information from the layer above it. An array of multiple-quantum-well (MQW) modulators is shown to be flipchip bonded to the silicon pixel array. An optical power bus (an integrated optical component) would deliver a readout beam to each modulator element in the array by means of an array of rib waveguides containing vertical-outcoupling gratings. Each diffractive optical element would provide weighted fanout connections from the modulator element of the corresponding pixel in the upper VLSI chip to the photodetectors of several neighboring pixels on the lower silicon VLSI chip.

This work was done by Armand R. Tanguay Jr., B. Keith Jenkins, Christoph von der Malsburg, Bartlett Mel, Irving Biederman, John O'Brien, and Anupam Madhukar of the University of Southern California for the Army Research Laboratory. For more information, download the Technical Support Package (free white paper) at www.defensetechbriefs.com/tsp  under the Photonics category. ARL-0013

Topics:
Architecture Fabrication Hardware Manufacturing processes Materials handling Mathematical models Optics Packaging Parts Photonics Research and development Sensors and actuators Simulation and modeling
This Brief includes a Technical Support Package (TSP).
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Adaptive Optoelectronic Eyes

(reference ARL-0013) is currently available for download from the TSP library.

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    Defense Tech Briefs Magazine

    This article first appeared in the April, 2007 issue of Defense Tech Briefs Magazine (Vol. 1 No. 2).

    Read more articles from the archives here.

    Overview

    The document is the final progress report for the research program titled "Adaptive Optoelectronic Eyes: Hybrid Sensor/Processor Architectures," which was conducted from June 1, 1998, to May 31, 2004, under the Multidisciplinary Research Program of the University Research Initiative. The program aimed to develop advanced vision systems that mimic the biological processes of mammalian vision, focusing on the integration of sensor and processor technologies in a compact, hybrid electronic/photonic multichip module.

    The report outlines significant accomplishments in two main areas: vision algorithms and models, and hybrid electronic/photonic hardware implementations. A key objective was to create a tightly coupled sensor/processor module that emulates the multilayer structure of the retina, facilitating efficient image acquisition and processing. The research explored various vision algorithms, including object recognition systems that utilize features inspired by mammalian vision, such as Gabor wavelets. This approach allowed for high accuracy in recognizing diverse objects in realistic environments.

    The document details the development of an invariant object recognition system, emphasizing the importance of robustness in recognizing objects despite variations in pose, scale, and depth. The research also included the extraction of shape-defining contours and the analysis of trade-offs in visual representations, contributing to a deeper understanding of feature learning in vision systems.

    Technologically, the program made strides in addressing the challenges of integrating multiple silicon VLSI vision chips into a hybrid architecture. This involved the use of novel diffractive optical structures for efficient interconnections and the characterization of key components like vertical cavity surface-emitting laser arrays (VCSELs) and diffractive optical elements (DOEs). The report highlights the interactions between vision algorithms and hardware implementations, which were crucial for the program's success.

    Despite the innovative advancements, the report notes that no patent applications were filed during the research period. However, there were significant interactions with Department of Defense agencies and corporations, indicating early stages of technology transfer for the research outcomes.

    Overall, the report encapsulates a multidisciplinary effort to advance the field of vision systems through the integration of biological principles, innovative algorithms, and cutting-edge hardware technologies, paving the way for future developments in adaptive optoelectronic eyes.

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