Ryan Benedic B. Yambao
ABSTRACT
Nowadays, canine parvovirus is a common virus that is spreading to dogs especially newborn puppies. The detection of this virus can be done in two ways; testing kit and laboratory. The testing kit is the popular testing, but the accuracy is low while the laboratory is that the results will come out 1 to 2 days. This paper presents another way of detecting the virus which is through image processing. It used a device that will help the experts at the laboratory to detect the virus. The device will be a raspberry pi that has a camera, and this device will be placed at the electron microscope's lens to detect whether the pathogen has a canine parvovirus or not. The SIFT algorithm and SVM were implemented to detect the parvovirus. The SIFT algorithm will help the device to extract the images of the pathogen of the virus while the SVM will classify whether the extracted data is a pathogen of a canine parvovirus or not.
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