Identification and Classification of Adenovirus Particles in Digital Microscopic Images using Active Contours

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Manjunatha Hiremath 1,*

1. Department of P. G. Studies and Research In Computer Science, Gulbarga University, Gulbarga-585106 Karnataka, India

* Corresponding author.


Received: 24 Mar. 2014 / Revised: 21 Apr. 2014 / Accepted: 10 May 2014 / Published: 8 Jun. 2014

Index Terms

Medical image processing, adenovirus, active contour multigrid, identification, classification


Medical imaging is the technique and process used to create images of the human body or medical science. Digital image processing is the use of computer algorithms to perform image processing on digital images. Microscope image processing dates back a half century when it was realized that some of the techniques of image capture and manipulation, first developed for television, could also be applied to images captured through the microscope. This paper presents semi-automated segmentation and identification of adenovirus particles using active contour with multi grid segmentation model. The geometric features are employed to identify the adenovirus particles in digital microscopic image. The min-max, 3 rules are used for recognition of adenovirus particles. The results are compared with manual method obtained by microbiologist.

Cite This Paper

Manjunatha Hiremath, "Identification and Classification of Adenovirus Particles in Digital Microscopic Images using Active Contours", International Journal of Modern Education and Computer Science (IJMECS), vol.6, no.6, pp.53-57, 2014. DOI:10.5815/ijmecs.2014.06.07


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