Mobile Vision-based Automatic Counting of Bacteria Colonies - Jacey-Lynn, Minoi; Tin, Tze Chiang; Terrin, Lim (IEEE, 2017)
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.