Characterization is mandatory to exploit potential of natural fibers since most them don’t have available datasheets. Coping with diameter disparity, lumen and their nature, the strength values of single natural fibers fluctuates substantially in a wide ranges. But, stiffness is relatively stable that it can be used to describe fibers and to make profound comparison among materials. Hence, appropriate stiffness estimation is needed and result accuracy is depending on various parameters that allow to calculate in a deterministic way. This paper describes a strategy to enhance stiffness estimation accuracy and precision employing direct and indirect measurement methods jointly with digital image correlation techniques. Enset fiber is used to display the efficacy of the methods. Using these methods, materials with known stiffness are considered as a benchmark and above 5% accuracy enhancement has been achieved compared with conventional method. The effect of errors can potentially lead to wrong conclusion about the properties of the material. Plus, the effect of each of the influencing parameter on stiffness result has been characterized. Thus, stiffness can be used to typifies the tensile property of a fiber and its estimation accuracy, which can be enhanced using digital image correlation, plays significant role to compare materials.