Scientific Results

Three-dimensional color object visualization and recognition using multi-wavelength computational holography

Year: 2007

Authors: Yeom S., Javidi B., Ferraro P., Alfieri D., De Nicola S., Finizio A.

Autors Affiliation: School of Computer and Communication Engineering, Daegu University, Jillyang, Gyeongbuk, Republic of Korea 712-714;
Dept. of Electrical and Computer Engineering, U-2157, University of Connecticut Storrs, CT USA 06269-2157;
CNR – Istituto Nazionale di Ottica Applicata, Via Campi Flegrei 34, 80078 Pozzuoli (NA), Italy;
Istituto di Cibernetica “E. Caianiello” del CNR, Via Campi Flegrei 34, 80078 Pozzuoli (NA), Italy

Abstract: In this paper, we address 3D object visualization and recognition with multi- wavelength digital holography. Color features of 3D objects are obtained by the multiple- wavelengths. Perfect superimposition technique generates reconstructed images of the same size. Statistical pattern recognition techniques: principal component analysis and mixture discriminant analysis analyze multi- spectral information in the reconstructed images. Class- conditional probability density functions are estimated during the training process. Maximum likelihood decision rule categorizes unlabeled images into one of trained- classes. It is shown that a small number of training images is sufficient for the color object classification. (c) 2007 Optical Society of America.

Journal/Review: OPTICS EXPRESS

Volume: 15 (15)      Pages from: 9394  to: 9402

KeyWords: digital holography
DOI: 10.1364/OE.15.009394

Citations: 36
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