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Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/578985
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dc.contributor.authorM. K. Hassan (UPM)
dc.contributor.authorN. F. H. Eko (UPM)
dc.contributor.authorS. Shafie (UPM)
dc.date.accessioned2023-11-06T03:11:56Z-
dc.date.available2023-11-06T03:11:56Z-
dc.date.issued2017-02
dc.identifier.issn0128-7680
dc.identifier.otherukmvital:116374
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/578985-
dc.descriptionTuberculosis (TB) is the second biggest killer disease after HIV. Therefore, early detection is vital to prevent its outbreak. This paper looked at an automated TB bacteria counting using Image Processing technique and Matlab Graphical User Interface (GUI) for analysing the results. The image processing algorithms used in this project involved Image Acquisition, Image Pre-processing and Image Segmentation. In order to separate any overlap between the TB bacteria, Watershed Segmentation techniques was proposed and implemented. There are two techniques in Watershed Segmentation which is Watershed Distance Transform Segmentation and Marker Based Watershed Segmentation. Marker Based Watershed Segmentation had 81.08 % accuracy compared with Distance Transform with an accuracy of 59.06%. These accuracies were benchmarked with manual inspection. It was observed that Distance Transform Watershed Segmentation has disadvantages over segmentation and produce inaccurate results. Automatic counting of TB bacteria algorithms have also been proven to be less time consuming, contains less human error and consumes less man-power.
dc.language.isoen
dc.publisherUniversiti Putra Malaysia Press
dc.relation.haspartPertanika Journals
dc.relation.urihttp://www.pertanika.upm.edu.my/regular_issues.php?jtype=2&journal=JST-25-S-2
dc.rightsUKM
dc.subjectAutomated bacteria counting
dc.subjectImage Processing
dc.subjectWatershed Segmentation
dc.subjectGraphical User Interface
dc.titleTuberculosis bacteria counting using watershed segmentation technique
dc.typeJournal Article
dc.format.volume25
dc.format.pages275-282
dc.format.issueSpecial Issue
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