Towards a colony counting system using hyperspectral imaging
2012
Colony counting is a procedure used in microbiology laboratories for food quality monitoring, environmental
management, etc. Its purpose is to detect the level of contamination due to the presence and growth of bacteria, yeasts
and molds in a given product. Current automated counters require a tedious training and setup procedure per product and
bacteria type and do not cope well with diversity. This contrasts with the setting at microbiology laboratories, where a
wide variety of food and bacteria types have to be screened on a daily basis. To overcome the limitations of current
systems, we propose the use of hyperspectral imaging technology and examine the spectral variations induced by factors
such as illumination, bacteria type, food source and age and type of the agar. To this end, we perform experiments
making use of two alternative hyperspectral processing pipelines and compare our classification results to those yielded
by color imagery. Our results show that colony counting may be automated through the automatic recovery of the
illuminant power spectrum and reflectance. This is consistent with the notion that the recovery of the illuminant should
minimize the variations in the spectra due to reflections, shadows and other photometric artifacts. We also illustrate how,
with the reflectance at hand, the colonies can be counted making use of classical segmentation and classification
algorithms.
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