Share Email Print
cover

Journal of Biomedical Optics

Automatic identification of biological microorganisms using three-dimensional complex morphology
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

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.

Paper Details

Date Published: 1 March 2006
PDF: 8 pages
J. Biomed. Opt. 11(2) 024017 doi: 10.1117/1.2187017
Published in: Journal of Biomedical Optics Volume 11, Issue 2
Show Author Affiliations
Seokwon Yeom, Univ. of Connecticut (United States)
Bahram Javidi, Univ. of Connecticut (United States)


© SPIE. Terms of Use
Back to Top