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An important factor that causes defect in the concrete structure is the systematic damage and it is very difficult to detect the cracks by visual examination. Digital image processing has proven to be one of the best substitutes for the monitoring of the cracks. A traditional filter based on image processing algorithm is a classical approach for monitoring the cracks. Thereafter, the deep learning-based methods have been implemented to detect and classify the cracks on the concrete images and have shown significant results. The convolution neural network-based models have fairly observed and graded the cracks giving better performance in terms of accuracy, precision and recall. After the bibliometric review of the existing literature, comparison of the performance of different models and existing methods can be observed.