Digital image analysis provides a simple, non-destructive approach for quantifying the visual characteristics of biomaterial membrane surfaces. This study evaluated bacterial cellulose–chitosan membranes impregnated with Centella asiatica extract at concentrations of 0%, 1%, 2%, and 3%, while maintaining a constant chitosan concentration. One full-resolution macroscopic image of each membrane was divided into ten non-overlapping regions of interest (ROIs), yielding a total of 40 ROI observations. Image processing was performed using Python to extract four color and intensity features, namely mean red, mean green, mean blue, and mean grayscale intensity, along with three texture features: contrast, homogeneity, and entropy. The analysis was conducted using a descriptive and exploratory approach, as each concentration was represented by only one membrane. The membrane containing 1% Centella asiatica extract exhibited the lowest mean grayscale intensity and the highest homogeneity, whereas the 2% membrane showed the highest mean grayscale intensity and the lowest homogeneity. The highest contrast value was observed in the 0% membrane, while the 2% and 3% membranes exhibited higher entropy values than the 0% and 1% membranes. These findings indicate that color and texture features provide complementary information for objectively characterizing visual differences and local heterogeneity among membrane formulations.
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