Pipelined algorithm and parallel architecture for real-time detection of sparse small objects in images

Mabo Robert Ito; Sinh Duong; John E. McFee; Kevin L. Russell

doi:10.1117/12.279518

29 October 1997 Pipelined algorithm and parallel architecture for real-time detection of sparse small objects in images

Mabo Robert Ito, Sinh Duong, John E. McFee, Kevin L. Russell

Proceedings Volume 3163, Signal and Data Processing of Small Targets 1997; (1997) https://doi.org/10.1117/12.279518
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

A pipe-lined algorithm and parallel architecture is under development for real time detection of sparse small objects in images. Monochromatic images from an airborne active infrared scanner, images from a low-altitude aircraft-mounted multispectral scanner, and passive infrared imagery obtained from cameras mounted on ground vehicle are the image types intended for the application of this system to the detection of minefields. The paper briefly describes the characteristics of these three different kinds of image sensors and the operating environments. The general image processing system architecture and the functions of each of the components are also presented. The feature selection and algorithm adaptations for each of the image classes are described. Preliminary results obtained from an experimental system consisting of a small transputer network and array processors are discussed.

Citation Download Citation

Mabo Robert Ito, Sinh Duong, John E. McFee, and Kevin L. Russell "Pipelined algorithm and parallel architecture for real-time detection of sparse small objects in images", Proc. SPIE 3163, Signal and Data Processing of Small Targets 1997, (29 October 1997); https://doi.org/10.1117/12.279518

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