An optical plant wellness and stress measuring system was developed based on the visual appearances of plants. Machine vision was used to quantify plants' wellness from side projected canopy images. A developed image analysing program calculated plants' leaf inclination state expressed in degrees, plant height and vertical centre of gravity at each hour during the experiments. To prevent stress and to ensure the wellness of the plants, a tolerable wilting rate can be set by the user. An irrigation pump was turned on automatically by the machine vision system to water the plants when the wilting rate was not tolerable. The image analyzing algorithm has several input files including preset parameters about the camera position, plants' stem and leaf parameters. These values can be changed for different plants cameras or measurements. Leaf inclination was measured by calculating local orientations expressed in degrees at each point on the visible leaf's edge lines. The leaves and stems on the image were separated according to the differences in their shape. Stems were defined as all the branches and petioles on the plant. 'Leaf and stem' direction was calculated from the angle of edge lines of all visible parts of the plant canopy, including leaves, petioles and branches. From the leaves' edge point directions a general leaf inclination value was estimated. The leaf inclination is given in degrees between 0 to -90, as the angle between the horizontal direction and that of the leaf direction. The optical monitoring system measures other shape, colour and size parameters of plant growth in vivo and in situ; continuously calculating the desired graphs and triggers actions according to parameters set by the user.