Automatic Detection and Pattern recognition of Morphological growth phases of Scenedesmus sp

Volume: 4    Issue: 6

Year of Publication: 2017

Pages: (1-6)

Authors: Sabeeha Sultana, Dr.Gowri Srinivasa, Dr.N Thajuddin

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Abstract

This study presents an automated system for identifying and classifying the growth patterns of Scenedesmus sp, a type of cyanobacteria. Different geometrical features associated with the species are used to detect, identify and classify cell growth patterns of the genera. The workflow proposed for segmentation comprises active contours and mathematical morphological operators and classification comprises a rule- based classifier or decision trees to delineate cell growth patterns as different morphological phases. The methods proposed have been compared against the gold standard – images segmented and labeled by human experts – and the results are found to be promising.

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Keywords

Cyanobacteria, Morphological operations, classification, active contours, senedesmus sp.