Evaluation of seedling growth rate using image processing

Planting high quality seed is the basis by which agriculture profit is gained. Commercially sold every seed lot has an assessment of seed quality which has a requirement of germinating seeds under different environmental conditions. Typically seed companies and commercial seed testing laboratories evaluate large number of seed lots each year, in the range of thousands. Seed testing, is currently done by humans and is slow and error prone. This research aims at creating seed analysis that will automate seed quality assessment. For this purpose, it is a need to an objective system which will provide consistent and correct results. After referring to different papers and keeping in mind the requirements, the system is designed which will measure the seedling size and growth rate using machine vision.