Research and implementation of yield recognition of Citrus reticulata based on target detection. Issue 1 (March 2021)

• Record Type: Journal Article
• Authors: Qin, Xiaoyue; Huang, Ruwei; Hua, Bei
• Is Part Of: Journal of physics. Volume 1820:Issue 1(2021)
• Publication Date: 2021-03
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1820/1/012128
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In order to effectively assess the yield of Citrus. This paper proposed a scheme to identify and calculate the size of the Citrus objects on the tree in order to achieve yield prediction which is based on the target detection technology and the principle of insinuation geometry. The results of the experiments show that, this scheme has good detection effect on the whole Citrustree or local multiple fruit on the tree in the field orchard whose correct rate of identification can reach 90% and recognition rate is as low as 1.006 frame per second. After manual measurement verification, the conFiguration achieved the accuracy of 80%. This paper is of great significance in the practicality of fast fruit counting, and the difficult problem of selecting Citrus, which consumes a supply of manpower, is solved preliminary.