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Optical Engineering

Target detection by co-occurrence matrix segmentation and its hardware implementation
Author(s): John Eric Auborn; James Martin Fuller; Howard M. McCauley
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Paper Abstract

A number of acquisition, tracking, and classification algorithms have been developed to deal with various image processing problems in the laboratory. Typically, these algorithms are too complicated to implement in a low-cost, real-time processor. Using image data in many real-time applications requires a system with very high data rates, low power dissipation, and a small packaging volume. We developed a processor architecture suitable for these applications, and adapted and demonstrated a co-occurrence matrix target detection algorithm in computer simulation and real-time hardware. A histogram, or gray-level distribution, is often used to select a threshold for image segmentation. This technique is often inadequate because the histograms tend to be noisy and exhibit many small peaks. Co-occurrence matrix-based segmentation allows homogeneous regions of an image to be identified and separated from a cluttered background. Results are shown for target segmentation using representative infrared imagery and real-time hardware.

Paper Details

Date Published: 1 November 1993
PDF: 5 pages
Opt. Eng. 32(11) doi: 10.1117/12.148105
Published in: Optical Engineering Volume 32, Issue 11
Show Author Affiliations
John Eric Auborn, Naval Air Warfare Ctr. (United States)
James Martin Fuller, Naval Air Warfare Ctr. (United States)
Howard M. McCauley, Naval Air Warfare Ctr. (United States)

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