Optical image processing and pattern recognition algorithms for optimal optical data retrieval

Brian Walker; Thomas Lu; Sean Stuart; George Reyes; Tien-Hsin Chao

doi:10.1117/12.2018264

29 April 2013 Optical image processing and pattern recognition algorithms for optimal optical data retrieval

Brian Walker, Thomas Lu, Sean Stuart, George Reyes, Tien-Hsin Chao

Proceedings Volume 8748, Optical Pattern Recognition XXIV; 87480L (2013) https://doi.org/10.1117/12.2018264
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

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.

Citation Download Citation

Brian Walker, Thomas Lu, Sean Stuart, George Reyes, and Tien-Hsin Chao "Optical image processing and pattern recognition algorithms for optimal optical data retrieval", Proc. SPIE 8748, Optical Pattern Recognition XXIV, 87480L (29 April 2013); https://doi.org/10.1117/12.2018264

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