Investigating strain localization at cracked concrete–sandstone specimens using optimized fractal theory-based image thresholding segmentation algorithm

The stability of concrete–rock interfaces is a critical issue in underground engineering. This study investigated the strain localization mechanism and energy evolution of concrete–sandstone specimens containing single and double interfacial cracks at various inclination angles. Acoustic emission (AE) technology and energy theory were used to analyze energy evolution, whereas digital image correlation was employed to examine strain development and fracture mechanisms. A new approach combining digital image processing and custom binarization was introduced to characterize the fractal properties of crack patterns using the box-counting method. Experimental results showed that the AE cumulative energy and stress–strain curves divided the loading process into three stages: crack closure (I), stable crack growth (II), and rapid crack propagation (III). Fractal dimensions were computed for both single- and double-crack specimens using the Otsu method and the proposed binarization technique. The Otsu method yielded values of 1.457, 1.482, 1.131, 1.512, 1.489, 1.536, 1.171, and 1.491, whereas the new method produced higher values—1.6038, 1.6643, 1.2713, 1.6806, 1.5594, 1.6282, 1.2239, and 1.6565—indicating enhanced fractal characteristics. Furthermore, the proposed method detected a three-phase evolution in fractal dimension before failure, which follows an initial increase, a stable period, and a final rapid rise. These findings provide theoretical support for the application of the proposed method in underground engineering. • The mechanical properties of the interface single crack specimens are superior to those of the interface double cracks specimens. • As the interface inclination angle increases, the mechanical properties of the specimen exhibit a trend of first increasing, then decreasing, and subsequently increasing again. • Fractal dimension of strain image calculated using improved threshold segmentation method is greater than that obtained by the traditional method. • The improved threshold segmentation method possesses more pronounced fractal characteristics.