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Proceedings Paper

Optical image processing and pattern recognition algorithms for optimal optical data retrieval
Author(s): Brian Walker; Thomas Lu; Sean Stuart; George Reyes; Tien-Hsin Chao
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Paper Abstract

Automatic pattern recognition algorithms are implemented to correct distortion and remove noise from the optical medium in the multi-channel optical communication systems. The post-processing involves filtering and correlation to search for accurate location of every optical data element. Localized thresholding and neural network training methods are used to accurately digitize the analog optical images into digital data pages. The goal is to minimize the bit-errorrate (BER) in the optical data transmission and receiving process. Theoretical analysis and experimental tests have been carried out to demonstrate the improved optical data retrieval accuracy.

Paper Details

Date Published: 29 April 2013
PDF: 12 pages
Proc. SPIE 8748, Optical Pattern Recognition XXIV, 87480L (29 April 2013); doi: 10.1117/12.2018264
Show Author Affiliations
Brian Walker, Georgia Institute of Technology (United States)
Thomas Lu, Jet Propulsion Lab. (United States)
Sean Stuart, Santa Monica College (United States)
George Reyes, Jet Propulsion Lab. (United States)
Tien-Hsin Chao, Jet Propulsion Lab. (United States)


Published in SPIE Proceedings Vol. 8748:
Optical Pattern Recognition XXIV
David Casasent; Tien-Hsin Chao, Editor(s)

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