Background <p>The accuracy of Digital Image Correlation is considerably influenced by the quality of images taken from the specimen surface. While previous have examined the impact of camera parameters on DIC results, the relationship between camera characteristics and DIC errors remains unclear.</p> Objective <p>In this study, a new theoretical model is introduced to estimate the DIC errors sourced from the camera.</p> Methods <p>The model is derived from the EMVA 1288 standard and contains camera gain, bit depth, and noise error. To validate the model, its results were compared with the real errors calculated from DIC results, and to determine the accurate error, various noise and gains effects were applied to digital images and then displacement and strain were numerically applied to these manipulated images and original images. The error calculated from the DIC successfully matched the error estimated by the model, proving the applicability of the models.</p> Results <p>The individual effects of noise, camera gain, and bit depth are analyzed separately, exploring their respective influences on the DIC. Subsequently, a simple formula is proposed to express camera performance in DIC.</p> Conclusions <p>Results showed that the DIC accuracy is considerably influenced by the camera gain, and temporal dark noise has a notable impact on DIC accuracy, particularly in scenarios with low-contrast speckle patterns. However, the influence of bit depth is negligible.</p>