The influence of surface texture on perceived whiteness (PW) of objects is examined. Ten woolen fabrics with different textures, knitted from the same yarn, were obtained and assessed for PW by a panel of observers previously. In this work we incorporated three factors, namely, roughness, directionality and density to represent image features of the scanned samples and determine whether a relationship between these features and PW is present. A correlation coefficient was used to examine the individual contribution of each factor to PW. A regression method was then developed to establish a model that related PW to these parameters. Results show that roughness is adversely related to PW while directionality and density are directly related to PW. Additional work is required to determine the role of these parameters on PW for a range of white substrates with different texture features. However, initial results indicate that the incorporating such parameters to indices of whiteness could potentially improve the correlation between visual and instrumental assessments of white objects. Results could also be potentially extended to colored objects.