Background

Bruising is the most common type of mechanical damage, which is inevitable along the postharvest chain, including harvesting, sorting, packaging and so on. It's the major cause of postharvest loss. However, the detection of bruises mainly relies on manual inspection which is time-consuming and mistake-prone, especially for the early bruises. In recent years, with the development of computer vision, more and more imaging techniques for real-time and automated bruise detection are proposed and studied again.

Scope and approach

This review provides an overview of recent advances in imaging techniques for bruise detection. The imaging techniques presented include spectral techniques (biospeckle imaging, hyperspectral/multispectral imaging, fluorescence imaging and structured-illumination reflectance imaging), nuclear magnetic techniques (magnetic resonance imaging and X-ray imaging) and thermal imaging. The basic principles of these imaging techniques and their application in bruise detection are concisely introduced.

Key findings and conclusion

The imaging techniques mentioned above exhibit potential to detect the bruised tissue and the bruise volume in real time and to overcome the fallibility, tediousness, destructiveness, and time-consumption, which are the disadvantages of traditional methods. In future research, integration of these techniques, developing specific algorithms for bruise detection and attempting to apply them into an assembly line for commercial value will be the research hotpots. In addition, the range of applications of these techniques for fruit and vegetable types also needs to be extended, and applying them in a practically assembly line should be enhanced.

中文翻译：

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水果和蔬菜挫伤检测成像技术的最新进展

背景

瘀伤是最常见的机械损伤类型，在收获后链中不可避免，包括收获，分拣，包装等。这是收获后损失的主要原因。然而，瘀伤的检测主要依靠人工检查，这是耗时且容易出错的，特别是对于早期瘀伤。近年来，随着计算机视觉的发展，提出了越来越多的实时自动挫伤检测成像技术并对其进行了研究。

范围和方法

这篇综述概述了用于瘀伤检测的成像技术的最新进展。提出的成像技术包括光谱技术（生物斑点成像，高光谱/多光谱成像，荧光成像和结构照明反射成像），核磁技术（磁共振成像和X射线成像）和热成像。简要介绍了这些成像技术的基本原理及其在瘀伤检测中的应用。

主要发现和结论

上述成像技术展现了实时检测瘀伤组织和瘀伤体积并克服易陷性，乏味，破坏性和耗时的潜力，这是传统方法的缺点。在未来的研究中，这些技术的集成，开发用于瘀伤检测的特定算法并试图将其应用于具有商业价值的装配线将是研究热点。另外，还需要扩展这些技术在水果和蔬菜类型上的应用范围，并且应该增强它们在实际装配线上的应用。