Share Email Print

Proceedings Paper

A proposed optical system for implementing the novel super-fast image processing scheme: the LPED method
Author(s): Chialun John Hu
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

LPED method, or Local Polar Edge Detection method, is a novel method the author discovered and implemented in many image processing schemes in the last 3 years with 3 papers published in this and other SPIE national conferences. It uses a special real-time boundary extraction method applied to some binary images taken by an uncooled IR camera on some high temperature objects embedded in a cold environment background in the far field. The unique boundary shape of each high temperature object can then be used to construct a 36D analog vector (a 36 − “digit” number U, with each “digit” being a positive analog number of any magnitude). This 36D analog vector U then represents the ID code to identify this object possessing this particular boundary shape. Therefore, U may be used for tracking and targeting on this particular object when this object is moving very fast in a 2D space and criss-crossing with other fast moving objects embedded in the same field of view. The current paper will report a preliminary optical bench design of the optical system that will use the above developed soft-ware to construct a real-time, instant-detect, instant track, and automatic targeting high power laser gun system, for shooting down any spontaneously launched enemy surface-to-air-missiles from the near-by battle ground. It uses the total reflection phenomenon in the Wollastron beam combiner and real-time monitor screen auto-targeting and firing system to implement this “instant-detect, instant-kill, SAM killer system”.

Paper Details

Date Published: 5 May 2014
PDF: 10 pages
Proc. SPIE 9094, Optical Pattern Recognition XXV, 90940D (5 May 2014); doi: 10.1117/12.2048571
Show Author Affiliations
Chialun John Hu, Southern Illinois Univ. at Carbondale (United States)
SunnyFuture Software (United States)

Published in SPIE Proceedings Vol. 9094:
Optical Pattern Recognition XXV
David Casasent; Tien-Hsin Chao, Editor(s)

© SPIE. Terms of Use
Back to Top