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Object Detection and Recognition Techniques Based on Digital Image Processing and Traditional Machine Learning for Fruit and Vegetable Harvesting Robots: An Overview and Review

Feng Xiao, Haibin Wang, Yaoxiang Li, Ying Cao, Xiaomeng Lv, Guangfei Xu

Year
2023
Citations
74
Access
Open access

Abstract

The accuracy, speed, and robustness of object detection and recognition are directly related to the harvesting efficiency, quality, and speed of fruit and vegetable harvesting robots. In order to explore the development status of object detection and recognition techniques for fruit and vegetable harvesting robots based on digital image processing and traditional machine learning, this article summarizes and analyzes some representative methods. This article also demonstrates the current challenges and future potential developments. This work aims to provide a reference for future research on object detection and recognition techniques for fruit and vegetable harvesting robots based on digital image processing and traditional machine learning.

Keywords

RobotRobustness (evolution)Artificial intelligenceImage processingComputer scienceDigital image processingCognitive neuroscience of visual object recognitionMachine visionDigital imageObject detection

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