| Technical and economical evaluation of the machine vision system to determine the percentage of breakage, impurity and number of wheat seeds |
| Paper ID : 1098-NICAME1402 |
| Authors: |
|
Mohammad Shaker *1, Adel Bakhshipour Ziaratgahi2, Dadgar Mohammadi3, Sayyed Mansour Alavimanesh4 1Agricultural Engineering Research Institute 2Faculty of Agricultural Sciences, University of Gilan 3Economic, Social and Extension Research Department, Fars Agricultural and Natural Resources Research and Education Center 4Agricultural Engineering Research Department, Fars Agricultural and Natural Resources Research and Education Center |
| Abstract: |
| In this research, a machine vision system was built and evaluated for two cultivars, Torabi and Azar wheat. This system consisted of three parts: suction box, sampling box and imaging box. In each type of wheat, the performance of the suction device was evaluated with two seed plates and four suction values. A completely randomized design with five replications was used for statistical analysis of data and Duncan test was used to compare means. In each amount of suction, the total number of seeds of sticked to the seed plate, the number of singled seeds and the seeds of sticked together on each hole were counted and their percentage was calculated. The image prepared by the digital camera was transferred to the MATLAB software and the algorithm for determining the percentage of breakage, the percentage of impurity and the number of wheat seeds was coded and validated. The results obtained from the research showed that the most suitable treatment for Turabi variety wheat was the seed plate with 1 mm holes and -100 mm Hg suction. For Azar variety wheat, the seed plate with 1 mm holes and suction of -120 mm Hg was the most suitable treatment. The validation results of the algorithm showed that its accuracy was close to 100%. The results of the economic study also showed that the decision to replace the machine vision system with the usual method has an economic justification in terms of the costs incurred. |
| Keywords: |
| Machine vision, breakage, impurity, wheat, image processing |
| Status : Paper Accepted (Oral Presentation) |
