Journal of Agricultural Big Data ›› 2022, Vol. 4 ›› Issue (1): 114-118.doi: 10.19788/j.issn.2096-6369.220117

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Image Data Set of Six Common Orchard Pests such as Bactrocera Dorsalis

Xianghe Zhang1,2(), Xiaoli Wang1,2,3, Tingting Liu1,2,3, Lin Hu1,2, Jingchao Fan1,2,3()   

  1. 1.Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing 100081
    2.National Agriculture Science Data Center, Beijing 100081
    3.Key Laboratory of Big Agri-Data, Ministry of Agriculture, Beijing 100081
  • Received:2021-12-20 Online:2022-03-26 Published:2022-06-29
  • Contact: Jingchao Fan E-mail:zhxianghe@163.com;fanjingchao@caas.cn

Abstract:

It is essential to use machine vision method for pest identification in orchard pest control and management. At present, most of the orchard pest image data collection centre on a single type and the resolution is inconsistent. In addition, only the original image data of pests are collected, and few data sets contain both the original image and the salient image of machine recognition. This data set includes 2412 image data of six common pests, such as bactrocera dorsalis, chafer, grapholitha molesta, leaf hopper, long icorn and bactrocera minax. Among them, 1613 original images were unprocessed. For images processed by deconvolution method, a total of 799 images with significant features were retained after eliminating the images with insignificant features. In conclusion, the data set can provide a data basis for the identification and classification of orchard pests.

Key words: orchard, pests identification, image data, machine recognition

CLC Number: 

  • S436.6