An Optically-Assisted 3-D Cellular Array Machine.

Abstract

The goal of this SBIR Phase II project was to develop a cellular array machine for real-time image processing. In this Phase II project, we developed a discrete-component based Cellular Neural Network (CNN) circuitry, which can perform CNN based analog image processing, such as edge detection and image enhancement, in real time. This prototyping system performs 3 x 3 cellular cells, and is interfaced with a video camera input and a monitor output. Live video is captured with the video camera and input to this CNN prototyping system for data processing. The result is then shown in the monitor in real-time. Figure 1-1 shows the setup of our demonstration system, in which one CCD video camera, two discrete-component based CNN boards, and one video TV monitor were used. Figure 1-2 shows the experimental results for real-time image edge detection operation. These results show that our discrete-component CNN prototyping system is functioning as we expected and may have a potential to turn into a commercialized product.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1997
Accession Number
ADA328910

Entities

People

  • Freddie Lin

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Automatic Gain Control
  • Change Detection
  • Computer Programming
  • Computers
  • Converters
  • Detection
  • Detectors
  • Digital Circuits
  • Digital Images
  • Image Processing
  • Instruction Set Architecture
  • Laser Diodes
  • Optical Interconnects
  • Processing Equipment
  • Semiconductors
  • Two Dimensional
  • Video Images

Fields of Study

  • Computer science

Readers

  • Image Processing and Computer Vision.
  • Integrated Circuit Design and Technology.
  • Parallel and Distributed Computing.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks