Defect detection based on singular value decomposition and histogram thresholding

This paper presents a novel method for defect detection based on singular value decomposition (SVD) and histogram thresholding. First, the input image is divided into blocks, where SVD is applied to determine if a region contains crack pixels. The detected crack blocks are then merged to construct a histogram to calculate the best binarization threshold by incoporating a recent technique for multiple peaks detection and Otsu algorithm. To validate the effectiveness and advantage of the proposed approach over related thresholding algorithms, experiments on images collected by an unmanned aerial vehicle have been conducted for surface crack detection. The obtained results have confirmed the merits of the proposed approach in terms of accuracy when using some well-known evaluation metrics.