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Design of a winter-jujube grading robot based on machine vision.
- Source :
-
Computers & Electronics in Agriculture . Jul2021, Vol. 186, pN.PAG-N.PAG. 1p. - Publication Year :
- 2021
-
Abstract
- • An automatic winter-jujube grading robot based on machine vision was designed. • A method combining YOLOv3 algorithm and hand-engineered features was developed to calculate the maturity of winter-jujube. • This method can detect overlapping winter-jujubes accurately and has a high stability under different lighting conditions. • The grading device has high ability to sort winter-jujube into three maturity categories. Winter-jujube is a kind of fresh fruit in China. After harvest, winter-jujubes require to grade into different categories according to their maturity levels. Mature winter-jujube can be recognized by their red colour. In this study, a winter-jujube grading robot is designed. Moreover, a method combining YOLOv3 algorithm and hand-engineered features is developed to calculate the maturity of winter-jujube. The grading robot is composed of a transmission unit, an image acquisition unit, and an actuator unit. Based on YOLOv3 algorithm, a detection model is trained, and compared with SSD and Faster R-CNN algorithms. When the IoU are 0.7, 0.8, and 0.9, the F1 scores of the model are 100%, 100%, and 93.66%, respectively. The mAP (IoU = 0.50:0.05:0.95) of the model is 94.78%, and the detection time of single image is 0.042 s. The detection model exhibits a high stability under different lighting conditions. In addition, overlapping winter-jujubes in the image can be detected accurately. After image distortion correction and object detection, an image processing flow for spatial positioning, size measurement and maturity calculation for winter-jujubes is designed. Finally, a real-time grading device for winter-jujube is built to perform grading experiments. The maturity grading accuracy is 97.28%, and the average grading time of each winter-jujube is 1.39 s. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01681699
- Volume :
- 186
- Database :
- Academic Search Index
- Journal :
- Computers & Electronics in Agriculture
- Publication Type :
- Academic Journal
- Accession number :
- 150874815
- Full Text :
- https://doi.org/10.1016/j.compag.2021.106170