International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Automatic Detection and Identification of Morphological Growth Patterns of Chroococcus Minutus

Author : Sabeeha Sultana ¹ Dr.Gowri Srinivasa ² Dr.Thajuddin ³

Date of Publication :7th June 2016

Abstract: The aim of the present study is to develop an automatic identification tool which is used to detect and classify the given Cyano bacterial digital cell images morphological stages. The different geometrical features are considered to detect, identify and classify the different morphological stages of blue- green algal cell such as about-to divide, normal and grownup. We propose a computerized method for segmentation and classification based on active contours and rule based classifier for the morphological phases of the Cyano bacterial images, and extracting the geometrical features associated with the segmented Cyano bacterial cell images. The experimental results that are obtained from this automated system are compared with the manual results obtained by human experts in the field of microbiology and discussed the efficiency and accuracy of the proposed system.

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