Extraction of Bacterial Clusters from Digital Microscopic Images through Statistical and Neural Network Approaches

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 174)


The field of bioinformatics shows a tremendous growth at the crossroads of biology, medicine, and informatics. Applying data mining techniques in the medical field is a very challenging undertaking due to the idiosyncrasies of the medical profession. Using conventional methods, it is very difficult to determine the exact number of microorganisms in a microscopic picture. In this paper, the emphasis is on the automatic detection of microbes using automated tools and extraction of bacterial clusters through statistical and neural network approaches. Also, Multiscan approaches with freeman chain code and contour detection for the bacterial patterns in the images have been presented. Experimental results shows that the bacterial cluster patterns obtained through neural network approach are better than the statistical approach.


Neural Network Approach Digital Microscopic Image Bacterial Cluster Apply Data Mining Technique Bacterial Pattern 


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© Springer India 2013

Authors and Affiliations

  1. 1.JSSATEBangaloreIndia
  2. 2.RNSITBangaloreIndia

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