Open Access
1 March 2006 Automatic identification of biological microorganisms using three-dimensional complex morphology
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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.
©(2006) Society of Photo-Optical Instrumentation Engineers (SPIE)
Seokwon Yeom and Bahram Javidi "Automatic identification of biological microorganisms using three-dimensional complex morphology," Journal of Biomedical Optics 11(2), 024017 (1 March 2006). https://doi.org/10.1117/1.2187017
Published: 1 March 2006
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CITATIONS
Cited by 13 scholarly publications and 6 patents.
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KEYWORDS
Microorganisms

3D image processing

Holograms

Digital holography

3D image reconstruction

Image segmentation

Holography

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