In the last decade, we have seen a tremendous emergence of genome sequencing analysis systems. These systems
are limited by the ability to phenotype numerous plants under controlled environmental conditions. To avoid
this limitation, it is desirable to use an automated system designed with plants control growth feature in mind.
For each experimental sequence, many parameters are subject to variations: illuminant, plant size and color,
humidity, temperature, to name a few. These parameters variations require the adjustment of classical plant
detection algorithms. This paper present an innovative and automatic imaging scheme for characterising the
plant's leafs growth. By considering a plant growth sequence it is possible, using the color histogram sequence,
to detect day color variations and, then, to compute to set the algorithm parameters. The main difficulty is to
take into account the automaton properties since the plant is not photographed exactly at the same position
and angle. There is also an important evolution of the plant background, like moss, which needs to be taken
into account. Ground truth experiments on several complete sequences will demonstrate the ability to identify
the rosettes and to extract the plant characteristics whatever the culture conditions are.