Abstract—An important process in sugarcane cultivation is sugarcane preparation and planting using billets with buds and rings. Manually cutting sugarcane into billets causes low quality and productivity for cultivation. Therefore, cutting machines are needed. A proper vision system aids the cutting machine. This study was to design a machine vision program to determine good rings on sugarcane billets. The algorithm was implemented using LabVIEW NI Vision 2015 and a web camera in an enclosed box. The test was performed on sugarcane billets harvested from a farm in Buriram, Thailand. The proposed vision system can determine the sizes of sugarcane billets, colors and locations of the rings. The method for determining rings was evaluating templates using their color spectra in HSL color space. The ring was identified by matching with templates using a color matching algorithm and identified position of rings by color location algorithm. The results of real time testing showed that the machine was able to identify rings correctly at 83.33% and identify the position of rings correctly at 73.81%.
Index Terms—agricultural automation, machine vision, sugarcane cutting machine
Cite: Akkaranat Rattanaphongphak and Wanwanut Boongsood, "Design of Machine Vision System for Sugarcane Buds or Rings Detection," Journal of Image and Graphics, Vol. 7, No. 3, pp. 102-106, September 2019. doi: 10.18178/joig.7.3.102-106
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