Automated counting of bacterial colonies on agar plates based on images captured at near-infrared light

Counting colonies is usually used in microbiological analysis to assess if samples meet microbiological criteria. Although manual counting remains gold standard, the process is subjective, tedious, and time-consuming. Some developed automatic counting methods could save labors and time, but their results are easily affected by uneven illumination and reflection of visible light. To offer a method which counts colonies automatically and is robust to light, we constructed a convenient and cost-effective system to obtain images of colonies at near-infrared light, and proposed an automatic method to detect and count colonies by processing images. The colonies cultured by using raw cows' milk were used as identification objects. The developed system mainly consisted of a visible/near-infrared camera and a circular near-infrared illuminator. The automatic method proposed to count colonies includes four steps, i.e., eliminating noises outside agar plate, removing plate rim and wall, identifying and separating clustered or overlapped colonies, and counting colonies by using connected region labelling, distance transform, and watershed algorithms, etc. A user-friendly graphic user interface was also developed for the proposed method. The relative error and counting time of the automatic counting method were compared with those of manual counting. The results showed that the relative error of the automatic counting method was −7.4%~ + 8.3%, with average relative error of 0.2%, and the time used for counting colonies on each agar plate was 11-21 s, which was 15-75% of the time used in manual counting, depending on the numbers of colonies on agar plates. The proposed system and automatic counting method demonstrate promising performance in terms of precision, and they are robust and efficient in terms of labor- and time-savings.