Partial differential equation-based enhancement and crack detection

Abstract

This paper presents an effective partial differential equation-(PDE-) based preprocessing algorithm for automated image-based crack detection. The proposed formulation combines various relevant and multiple processes such as contrast and selective edge enhancement in addition to edge-preserving smoothing to enhance the image prior to detection. The approach is adaptive and controlled by reliable image metrics to determine the stopping time of the PDE ensuring optimum results for various images. Additionally, a simplified thresholding algorithm based on local global maximum gradient matching is used to extract the crack features from the image. The proposed scheme does not require arbitrary or manually tuned parameters nor a large dataset for training to obtain good results. Experiments indicate that the proposed approach performs better when compared to several other algorithms in the literature.