Rapeseed seeds colour recognition by machine vision

Rapeseed is one of the important oilseed crop species, and is worldwide the most important economically. The light seed colour in rapeseed is associated with improved oil, protein and fibre contents. But there are not reliable and efficient methods to measure seed colour, especially the single seed colour. Two transformations of RGB (red, green, and blue) colour space were used for two seed colour recognition methods, i.e., HSV (hue, saturation, and value) and nine colour model (NCM). Using these two colour space transformations, the performance of the common method on rapeseed colour recognition was compared with the major colour method. The common method obtained the colour recognition accuracy of 83.96% in single seed recognition and 92.72% in sample recognition. The major colour method obtained the colour recognition accuracy of 98.91% in single seed recognition and 100% in sample recognition. The major colour method combined with HSV and NCM colour space transformation proved to be a good approach for seed colour recognition of rapeseed using machine vision.