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Proceedings Paper

Automatic screening and multifocus fusion methods for diatom identification
Author(s): Manuel Forero; Filip Sroubek; Jan Flusser; Rafael Redondo; Gabriel Cristobal
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Paper Abstract

The first part of this paper presents a new method for the classification and screening of diatoms in images taken from water samples. The technique can be split into three main stages: segmentation, object feature extraction and classification. The segmentation part consists of two modified thresholding and contour tracing techniques in order to detect the majority of objects present at the sample. From the segmented objects, several features have been extracted and analyzed. For the classification, a diatom training set was considered and the centroids, means and variances of four different classes were found. For the identification process diatoms were classified according with their Mahalanobis distance. The results show the method ability to select at least 80% of usable diatoms from images contaminated with debris. Secondly, full automation of the diatom classification is achieved when multi-focal microscopy is utilized for water sample acquisition. In this case, a necessary preprocessing step is image fusion. A novel wavelet-based fusion method proposed here returns a sharp image that can be directly used for segmentation. For a better understanding of the diatom shape, a 2.5D reconstruction is given.

Paper Details

Date Published: 30 December 2003
PDF: 10 pages
Proc. SPIE 5200, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation VI, (30 December 2003); doi: 10.1117/12.506841
Show Author Affiliations
Manuel Forero, Instituto de Optica/CSIC (Spain)
Filip Sroubek, Institute of Information Theory and Automation (Czech Republic)
Jan Flusser, Institute of Information Theory and Automation (Czech Republic)
Rafael Redondo, Instituto de Optica/CSIC (Spain)
Gabriel Cristobal, Instituto de Optica/CSIC (Spain)


Published in SPIE Proceedings Vol. 5200:
Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation VI
Bruno Bosacchi; David B. Fogel; James C. Bezdek, Editor(s)

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