The present work aimed to develop an efficient way of capturing real-time crack propagation in concrete structures. The image processing was utilized for crack detection, while finite element modeling (FEM) and scanning electron microscopy (SEM) were used for quantitative and qualitative analysis of crack propagation. A green cement-based composite (CBC) containing saw dust was compared to a reference M20 grade concrete under compressive loading. Crack propagation during compression tests was captured using an 8-megapixel mobile phone camera. The randomly selected images showing crack initiation and propagation in CBCs were used to assess the crack capturing capability of a spectral analysis based algorithm. A measure of oriented energy was provided at crack edges to develop a similarity spatial relationship among the pairwise pixels. FE modelling was used for distress anticipation, by analyzing stresses during the compressive test in constituents of CBCs. SEM analyses were also done to evaluate cracked samples. It was found that FE modeling could predict the crack prone regions that can be used jointly with the image analysis algorithm, providing real-time inputs from the crack-prone areas. Green CBC were compared to reference concrete samples, showing reliable results. The replacement of OPC with wood dust reduced compression strength and produced a different fracture pattern regarding reference concrete. The results of the study can be used for distress anticipation and early crack detection of concrete structures for preventive support and management.