•Image texture analysis is used to characterize micrographs and fractographs.•Fractal analysis, GLCM and RLS analysis have been carried out.•Systematic variation of texture descriptors with ageing temperature.•Correlation of texture descriptors vis-à-vis mechanical properties.•The concept of automatic characterization with machine vision has been highlighted. Texture analyses methods incorporating fractal analysis using box-counting, grey level co-occurrence matrix (GLCM) technique and run length statistical (RLS) analysis technique have been carried out to automatically characterize micrographs and fractographs of Cu-strengthened high-strength low alloy (HSLA) steel. The selected steel has been solution treated and water quenched followed by ageing at different temperatures. Tensile tests have been carried out for water quenched and aged specimens. Microstructural and fractographic analyses are made using scanning electron microscope. Ten texture features from the three texture analyses methods are extracted to correlate with the observed mechanical properties. The obtained image texture features of both micrographs and fractographs have been compared with the estimated mechanical properties. The results obtained from the investigation reveal that there is a systematic correlation of the mechanical properties and image texture features with ageing temperatures.