RESEARCH ON RECOGNITION OF OCCLUDED ORANGE FRUIT ON TREES BASED ON YOLOv4-Reference-Cited by-同舟云学术

RESEARCH ON RECOGNITION OF OCCLUDED ORANGE FRUIT ON TREES BASED ON YOLOv4

Published:2022-08-31 Issue: Volume: Page:137-146
ISSN:2068-2239
Container-title:INMATEH Agricultural Engineering
language:en
Short-container-title:INMATEH

Author:

LI Yan¹,XIAO Liming¹,LI Weiq¹,LI Hao¹,LIU Jie²

Affiliation:

1. College of Engineering, Huazhong Agricultural University, Wuhan, Hubei/ China

2. College of Engineering, Huazhong Agricultural University, Wuhan, Hubei/ China, Key Laboratory of Agricultural Equipment in Mid-lower Yangtze River, Ministry of Agriculture and Rural Affairs, Wuhan, Hubei/ China, Citrus Mechanization Research Base, Ministry of Agriculture and Rural Affairs, Wuhan, Hubei/ China

Abstract

For accurate recognition of orange fruit targets, a detection algorithm based on YOLOv4 was applied in this research. The results showed that AP (average precision) of YOLOv4 had reached 98.17%, 2.14% and 2.67% respectively higher than SSD and Faster RCNN while recognition rate of traditional image processing algorithms was merely 54.94%. Additionally, the extent of occlusion was proved to have obvious influences on the accuracy of orange detection. The accuracy on slight occlusion conditions appeared to be higher than that on serious occlusion conditions. Generally, YOLOv4 detection algorithm showed its feasibility and superiority on fruit detection in the complex natural environment.

Publisher

INMA Bucharest-Romania

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering,Food Science

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