The Identification of Parasite Babesia Form on Cow Blood by Using Active Contour Model
<p class="BasicParagraph">Babesia parasite is one of the parasites that infect the cow blood and it can cause death. Observation of blood data sample in the laboratory used a microscope equipped by optilab cameras. The form of microscopic observation of a blood must be supported by t...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | Indonesian |
| Published: |
Universitas Sultan Agneg Tirtayasa
2017-10-01
|
| Series: | Volt: Jurnal Ilmiah Pendidikan Teknik Elektro |
| Subjects: | |
| Online Access: | http://jurnal.untirta.ac.id/index.php/VOLT/article/view/2136 |
| Summary: | <p class="BasicParagraph">Babesia parasite is one of the parasites that infect the cow blood and it can cause death. Observation of blood data sample in the laboratory used a microscope equipped by optilab cameras. The form of microscopic observation of a blood must be supported by the skill of the observer to determine whether the blood is parasitic or not. This study aims to find the method of automatic search of parasite Babesia sp form by using the method of active contour model (ACM). Parasite in the blood is very likely to be detected by utilizing the science of image processing. One of the science image processing is Active Contour Model. Initial data in the form of image file was the result from the shoot using camera optilab and it had RGB color. The first data processing was done by doing the color conversion to be homogeneous and facilitated the Active Contour Model works. The preprocessing process invented the RGB-HSV-grayscale-binary/ BW conversion method. HSV was used to remove colors considered as noise. To reinforce the parasite object, the background was converted to grayscale, then the removed image of the noise color and the grayscale back-ground were converted to binary imagery. This research finds the method of Active Contour Model which can do maximum cropping on the binary image. In the grayscale image, there were still constraints with the edges of the contrast blood form with the background. The result of the implementation of Active Contour Model had accuracy 0.997, Sensitivity 0.99, Specificity 74%.</p> |
|---|---|
| ISSN: | 2528-5688 2528-5696 |