Kiwifruit recognition at nighttime using artificial lighting based on machine vision - Longsheng, Fu; Bin, Wang; Yongjie, Cui; Shuai, Su; Gejima, Yoshinori; Kobayashi, Taiichi (International Journal of Agricultural and Biological Engineering, 2015)
Most researches involved so far in kiwifruit harvesting robot suggest the scenario of harvesting in daytime for taking advantage of sunlight. A robot operating at nighttime can overcome the problem of low work efficiency and would help to minimize fruit damage. In addition, artificial lights can be used to ensure constant illumination instead of the variable natural sunlight for image capturing. This paper aims to study the kiwifruit recognition at nighttime using artificial lighting based on machine vision. Firstly, an RGB camera was placed underneath the canopy so that clusters of kiwifruits could be included in the images. Next, the images were segmented using an R-G color model. Finally, a group of image processing conventional methods, such as Canny operator were applied to detect the fruits. The image processing results showed that this capturing method could reduce the background noise and overcome any target overlapping. The experimental results showed that the optimal artificial lighting ranged approximately between 30-50 lx. The developed algorithm detected 88.3% of the fruits successfully.Keywords: Elliptic Hough transform, image capturing method, Kiwifruit, minimal bounding rectangle, optimal illumination intensityDOI: 10.3965/j.ijabe.20150804.1576Citation: Fu L S, Wang B, Cui Y J, Su S, Gejima Y, Kobayashi T. Kiwifruit recognition at nighttime using artificial lighting based on machine vision. Int J Agric & Biol Eng, 2015; 8(4): 52－59.