Abstract: This paper focuses on the civil engineering field. By leveraging machine vision technology to identify images of collected concrete products, it can rapidly, accurately, and non - destructively assess their performance, which is of great significance for engineering applications. Currently, traditional manual inspection methods are inefficient and highly subjective. Meanwhile, existing image recognition technologies face challenges such as uneven lighting, background noise interference, diverse crack shapes, and blurry boundaries in dynamic images. There is an urgent need to construct intelligent solutions that can adapt to complex engineering scenarios. Through a systematic review of relevant literature, the research focuses on the assessment of two types of concrete, namely the identification of cracks and appearance defects in static hardened concrete, and the evaluation of the flowability of dynamic fresh concrete. Firstly, from the perspectives of traditional digital image technology and neural networks, it reviews the research progress of existing studies on crack identification, appearance quality discrimination, and flowability assessment under different scenarios and shooting subjects. Then, it summarizes and compares the advantages and disadvantages of different algorithms in the steps of preprocessing, image segmentation, and feature extraction in the existing processing procedures, as well as their application scenarios. Finally, through comparative analysis, a set of recommended image recognition processing procedures and solutions for judging the appearance quality and flowability of concrete products is proposed. This provides algorithmic ideas for the intelligent recognition and assessment of structural concrete performance, promoting the application of visual technology in the civil engineering field.

摘要： 在土木工程领域，借助机器视觉技术，对采集的混凝土产品图像进行识别，可快速、准确且无损地评估其性能，对于工程应用具有重大意义。当前，传统人工检测方法效率低、主观性强，而现有图像识别技术面临光照不均、背景噪声干扰、裂缝形态多样、动态图像分界模糊等挑战，亟需构建适应复杂工程场景的智能化解决方案。通过系统梳理有关文献，研究聚焦两种状态混凝土评估，即静态硬化混凝土裂缝与外观缺陷识别、动态新拌混凝土流动性能评估。首先，从传统数字图像技术角度和神经网络角度分别综述了现有研究在不同场景和拍摄主体下、对于裂缝识别、外观质量判别、流动性评估的研究进展；接着，总结对比了现有处理流程中预处理、图像分割、特征提取等步骤中不同算法的优劣与应用场景；最后，通过对比分析提出了一套推荐的混凝土产品外观质量和流动性判断的图像识别处理流程和解决方案，为结构混凝土性能的智能识别与评估提供了算法思路，以促进视觉技术在土木工程领域的应用。