Three-dimensional color object visualization and recognition using multi-wavelength computational holography
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 holographyDOI: 10.1364/OE.15.009394Citations: 36data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2020-05-31References taken from IsiWeb of Knowledge: (subscribers only)Connecting to view paper tab on IsiWeb: Click hereConnecting to view citations from IsiWeb: Click here