Software Application in Machine Vision Investigation of Agricultural Seeds Quality
The paper tries to analyze the possibilities of classification of hemp fiber plant seeds in order to provide an image recognition sorting system that can estimate the quality of the fiber hemp seeds destined for human consumption. Systems that can optically grade cereal grains are already available in the agricultural industry. The automatic classification systems for seeds take in consideration the size, shape, color and texture in order to assess the quality of nutritional seeds.This work investigates the classification possibilities of image systems using photo images acquired by an RGB camera. The article presents the experimental stand and devices used for the image analysis of the fiber hemp seeds probes. The method for the selection of the representative pixels of the quality seeds is described and finally the results for the classification of the ratio of ripe seeds versus unripe seeds are presented in graphs. Conclusions are formulated and discussed.
D. Ola et al., "Software Application in Machine Vision Investigation of Agricultural Seeds Quality", Applied Mechanics and Materials, Vol. 436, pp. 463-473, 2013