为改善传统裂缝识别算法抗干扰能力差、识别精度低等问题，通过改进现有种子填充算法，建立了混凝土表存裂缝图像识别系统，实现了裂缝信息的准确提取。预处理中，提出光照不均匀系数筛选算法对图像进行快速筛选，提高了匀光处理效率；裂缝识别中，对既有种子填充算法进行了改进，使之能自动确定裂缝的生长点，并结合八方向搜索方式和相对阈值法的边界判断实现了裂缝的图像分割，最后利用连通域滤波剔除了一系列复杂背景干扰；在特征提取阶段通过引入形态学处理、毛刺剔除及节点欧式距离等手段，准确获取了裂缝条数、长宽等量化信息。与传统混凝土裂缝图像识别算法相比，该图像识别系统实现了效率和精度更大程度的统一，且裂缝长、宽值的提取误差控制在了10%以内。

In order to solve the problems of poor anti-interference ability and low recognition accuracy of traditional crack identification algorithms，an image identification system for concrete surface existing cracks was established by improving the existing seed filling algorithm to achieve accurate extraction of crack information.In the pre-processing，the illumination uneven coefficient screening algorithm was proposed to quickly screen the image，which improves the efficiency of uniform light processing.In the crack identification，the existing seed filling algorithm was improved，so that it can automatically determine the growth point of the crack.And the image segmentation of the crack was realized by combining the eight-direction search method with the boundary judgment of the relative threshold method.Then a series of complex background interference were eliminated with the connected domain filter.In the feature extraction stage，by introducing morphological processing，burr removal and node Euclidean distance，the quantitative information of the number of cracks，length and width was accurately obtained.Compared with traditional concrete crack image recognition algorithms，this algorithm achieves a greater degree of unification of efficiency and accuracy，and the extraction error of the crack length and width values is controlled within 10%.