Jacey-Lynn, Minoi and Tin, Tze Chiang and Terrin, Lim (2017) Mobile Vision-based Automatic Counting of Bacteria Colonies. International Conference on Information and Communication Technology (ICICTM). ISSN ISBN: 978-1-5090-0412-6
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Abstract
The procedure for counting colonies is often performed manually and the process is lengthy and tedious. For that reason, several methods that rely on digital images for automatically counting cells and bacteria colonies have been proposed. Fully automated and high throughput hardware imaging instruments are also available, but such machines are extremely costly. In this paper, we introduce a mobile based computer vision algorithm for automatic bacteria colony counting using morphological operations and transforms in image processing, on a custom Android mobile cross-platform open source software and written in Java, C++ and Open CV computer vision library. The results have shown are promising given that the acquisition and detection were done in a noncontrolled environment.
| Item Type: | Article |
|---|---|
| Additional Information: | Information, Communication and Creative Technology |
| Uncontrolled Keywords: | Colony counting, Hough transform, wavelet, Image segmentation, Transforms, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology |
| Depositing User: | Karen Kornalius |
| Date Deposited: | 15 Jun 2017 01:04 |
| Last Modified: | 09 Jan 2024 03:41 |
| URI: | http://ir.unimas.my/id/eprint/16656 |
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