果实检查和分类的人工视觉系统:系统文献综述
Ignacio Rojas Santelices1, Sandra Cano2, Fernando Moreira3,4
1Doctorate in Smart Industry, Pontificia Universidad Católica de Valparaíso, Avenida Brasil 2141, Valparaiso 2370688, Chile.
Sensors (Basel, Switzerland)
|March 17, 2025
概括
计算机视觉增强了水果分类和质量检查. 本综述详细介绍了用于提高水果安全性和行业标准的应用程序,硬件 (RGB,多光谱摄像头) 和算法 (传统,深度学习).
科学领域:
- 农业工程 农业工程
- 计算机视觉 计算机视觉
- 食品科学 食品科学 食品科学
背景情况:
- 计算机视觉对于确保水果行业的质量和安全至关重要.
- 自动化水果分类系统需要高效准确的检查技术.
- 现有的文献涵盖了各种方面,但缺乏对当前实践的综合概述.
研究的目的:
- 系统地审查和识别基于计算机视觉的果实分类应用程序,硬件和算法.
- 提供有关水果质量检查的最新情况的全面概述.
- 引导开发先进的水果分类系统.
主要方法:
- 按照PRISMA方法论进行系统的文献综述.
- 分析了2015年至2024年间发表的56篇文章,这些文章来自Web of Science和Scopus.
- 根据应用领域,硬件配置和处理技术对发现进行分类.
主要成果:
- 确定了主要的应用领域:果园,工业加工,零售/家庭环境.
- 主要的硬件包括RGB摄像头和LED照明;多光谱摄像头对于诸如异物检测等复杂任务至关重要.
- 常见的处理技术范围从传统的算法 (Otsu,Sobel) 到深度学习模型 (ResNet,VGG),通常利用转移学习.
结论:
- 该研究为开发水果质量检查和分类系统提供了基本指南.
- 不同的环境需要量身定制的硬件和算法方法来实现最佳性能.
- 计算机视觉技术的进步,特别是深度学习,正在改变水果分类和质量评估.
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