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Research Papers

Automatic identification of biological microorganisms using three-dimensional complex morphology

[+] Author Affiliations
Seokwon Yeom, Bahram Javidi

University of Connecticut, Electrical and Computer Engineering Department, 371 Fairfield Road, Unit 2157, Storrs, Connecticut 06269-2157

J. Biomed. Opt. 11(2), 024017 (March 24, 2006). doi:10.1117/1.2187017
History: Received August 24, 2005; Revised November 22, 2005; Accepted December 02, 2005; Published March 24, 2006
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We propose automated identification of microorganisms using three-dimensional (3-D) complex morphology. This 3-D complex morphology pattern includes the complex amplitude (magnitude and phase) of computationally reconstructed holographic images at arbitrary depths. Microscope-based single-exposure on-line (SEOL) digital holography records and reconstructs holographic images of the biological microorganisms. The 3-D automatic recognition is processed by segmentation, feature extraction by Gabor-based wavelets, automatic feature vector selection by graph matching, training rules, and a decision process. Graph matching combined with Gabor feature vectors measures the similarity of complex geometrical shapes between a reference microorganism and unknown biological samples. Automatic selection of the training data is proposed to achieve a fully automatic recognition system. Preliminary experimental results are presented for 3-D image recognition of Sphacelaria alga and Tribonema aequale alga.

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© 2006 Society of Photo-Optical Instrumentation Engineers

Citation

Seokwon Yeom and Bahram Javidi
"Automatic identification of biological microorganisms using three-dimensional complex morphology", J. Biomed. Opt. 11(2), 024017 (March 24, 2006). ; http://dx.doi.org/10.1117/1.2187017


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