surface-crack

surface crack images classification using CNN

Dataset

The datasets contain images of various concrete surfaces with and without crack. The image data are divided into two as negative (without crack) and positive (with crack) in separate folder for image classification. Each class has 20000 images with a total of 40000 images with 227 x 227 pixels with RGB channels.

Surface Crack dataset is generated from 458 high-resolution images (4032x3024 pixel) with the method proposed by Zhang et al (2016). High resolution images found out to have high variance in terms of surface finish and illumination condition. No data augmentation in terms of random rotation or flipping or tilting is applied.

Check out the detailed description, code and results in my GitHub repository.

Figure 1. Some of surface crack detection results: False Positive samples from the test set.
Figure 1. Some of surface crack detection results: False Negative samples from the test set.