农机化研究2025，Vol.47Issue(7)：59-64,6.DOI:10.13427/j.issn.1003-188X.2025.07.008
基于YOLOv7和YCrCb的火龙果识别与分割方法
Identification and Segmentation Method of Dragon Fruit Based on YOLOv7 and YCrCb
摘要
Abstract
At the current stage,dragon fruits are primarily harvested manually.Delayed harvesting can result in less freshness of fruits,leading to a loss in fruit quality and compromising their storage potential.To address these issues,the research on developing dragon fruit harvesting robots for automation has become an important initiative.Image recognition and segmentation of dragon fruits play a crucial role in achieving automated harvesting.For this,proposed an algorithm that combines YOLOv7 and the YCrCb color space for the recognition and segmentation of dragon fruits in the complex background.The algorithm utilized the YCrCb color space in conjunction with methods such as the OTSU threshold seg-mentation algorithm and morphological operations to segment the fruit from the background within the detection boxes of the YOLOv7 network.In order to evaluate the performance of the YOLOv7 network,a comparison was made with the Faster R-CNN network under the same experimental conditions.The results showed that the average detection accuracy of YOLOv7 improved by 6.81%to 98.82%,and the F1 score increased by 0.22 to 0.95.Additionally,the YCrCb col-or space allowed for effective segmentation of dragon fruits with an average processing time of approximately 108 ms.关键词
火龙果/YOLOv7/图像分割/YCrCb/OTSU算法Key words
dragon fruit/YOLOv7/image segmentation/YCrCb/OTSU algorithm分类
农业科技引用本文复制引用
罗陈迪,李文涛,商枫楠,肖明玮,陈桥,欧阳春凡,周学成..基于YOLOv7和YCrCb的火龙果识别与分割方法[J].农机化研究,2025,47(7):59-64,6.基金项目
广东省科技计划项目(2021B1212040009) （2021B1212040009）
