Simple Search:

Tuberculosis bacteria counting using watershed segmentation technique


Citation

Hassan, Mohd Khair and Eko Sukohidayat, Nurul Farah Hidayah and Shafie, Suhaidi (2017) Tuberculosis bacteria counting using watershed segmentation technique. Pertanika Journal of Science & Technology, 25 (spec. Feb.). pp. 275-282. ISSN 0128-7680; ESSN: 2231-8526

Abstract / Synopsis

Tuberculosis (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.


Download File

[img]
Preview
PDF
32-JTS(S)-0146-2016-4thProof.pdf

Download (1MB) | Preview

Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
Institute of Advanced Technology
Publisher: Universiti Putra Malaysia Press
Keywords: Automated bacteria counting; Image processing; Watershed segmentation; Graphical user interface
Depositing User: Nabilah Mustapa
Date Deposited: 30 Jun 2017 17:50
Last Modified: 05 Jul 2017 11:32
URI: http://psasir.upm.edu.my/id/eprint/55892
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item